updated: 20.06.2024

List of Publications by Edmond J. Safra Center Fellows


589. Algavi, Y. M., Borenstein, E (2024)  Relative dispersion ratios following fecal microbiota transplant elucidate principles governing microbial migration dynamics. Nat Commun 15, 4447 (2024).


588. Azouri D, Granit O, Alburquerque M, Mansour Y, Pupko T, Mayrose I. (2024) The tree reconstruction game: phylogenetic reconstruction using reinforcement learning. Molecular biology and evolution, .


587. R. Sheinin, K. Salomon, E. Yeini, S. Dulberg, A. Kaminitz, R. Satchi-Fainaro, R. Sharan & A. Madi (2024) interFLOW: maximum flow framework for the identification of factors mediating the signaling convergence of multiple receptors. npj Syst Biol Appl 10, 66 (2024).


586. D. Miller, O. Arias and D. Burstein (2024) GeNLP: a web tool for NLP-based exploration and prediction of microbial gene function. Bioinformatics, Volume 40, Issue 2, February 2024, btae034,


585. N. Liscovitch-Brauer, R. Mesika, T. Rabinowitz, H. Volkov, M. Grad , R. Tomashov Matar , L. Basel-Salmon , O. Tadmor , A. Beker , N. Shomron (2024) Machine learning-enhanced noninvasive prenatal testing of monogenic disorders. Prenat Diagn,  2024 Apr 30. doi: 10.1002/pd.6570. 


584. Wygoda, E., Loewenthal, G., Moshe, A., Alburquerque, M., Mayrose, I., and Pupko, T. (2024) Statistical framework to determine indel length distribution. Bioinformatics, 40(2):btae043.


583. Nagar, N., Tubiana, J., Loewenthal, G., Wolfson, H.J., Ben-Tal, N., and Pupko, T. (2023)  EvoRator2: predicting site-specific amino acid substitutions based on protein structural information using deep learning. Journal of Molecular Biology: 435(14):168155.


582. Dotan, E., Jaschek, G., Pupko, T., and Belinkov, Y. (2024) Effect of tokenization on transformers for biological sequences. Bioinformatics. 40(4):btae196.


581. A. Zorea, D. Pellow, L. Levin, S. Pilosof, J. Friedman, R. Shamir, I. Mizrahi (2024) Plasmids in the human gut reveal neutral dispersal and recombination that is overpowered by inflammatory diseasesNat Communications 15, Article number: 3147, (2024).


580. H. Levi, R. Elkon, R. Shamir (2024) The predictive capacity of polygenic risk scores for disease risk is only moderately influenced by imputation panels tailored to the target populationBioinformatics, btae036,


579. Poppenwimer T, Mayrose I, De-Malach N. (2023) Revising the global biogeography of annual and perennial plants. Nature, 624:109–114. 


578. R. Danino, I Nachman, R Sharan (2023) Batch correction of single-cell sequencing data via an autoencoder architecture. Bioinformatics Advances, Volume 4, Issue 1, 2024, vbad186,


577. D. Pellow, L. Pu, B. Ekim, L. Kotlar, B. Berger, R. Shamir, Y. Orenstein (2023) Efficient minimizer orders for large values of $k$ using minimum decycling setsGenome Research DOI: 10.1101/gr.277644.123.


576. H. Levi, S. Carmi, S. Rosset, R. Yerushalmi, A. Zick, T. Yablonski-Peretz, .... (127 members of the BCAC Consortium)..., S. Ben-Shachar, N. Elefant*, R. Shamir* and R. Elkon*. Evaluation of European-based polygenic risk score for breast cancer on Ashkenazi Jewish womenJ. of Medical Genetics, doi:10.1136/jmg-2023-109185 (2023).


575. Y. Itai, N. Rappoport, R. Shamir (2023) Integration of gene expression and DNA methylation data across different experiments. Nucleic Acids Research, gkad566, (2023).


574. N. Rappaport, E. Chomsky, T. Nagano, C. Seibert, Y. Lubling, Y. Baran, A. Lifshitz, W. Leung, Z. Mukamel, R. Shamir, P. Fraser, A. Tanay (2023) Single cell Hi-C identifies plastic chromosome conformations underlying the gastrulation enhancer landscapeNat Communications 14(1):3844. doi: 10.1038/s41467-023-39549-4.


573. Peretz, I., Kupiec M.* and R. Sharan* (2022) A comparative analysis of telomere length maintenance circuits in fission and budding yeast. Frontiers in Genetics 13:1033113. doi: 10.3389/fgene.2022.1033113.


572. Muller, E., Shiryan, I. & Borenstein, E. (2024) Multi-omic integration of microbiome data for identifying disease-associated modules. Nat Commun 15, 2621 (2024).


571. Lynn, N., Tuller, T. (2024) Detecting and understanding meaningful cancerous mutations based on computational models of mRNA splicing. npj Syst Biol Appl 10, 25 (2024).


570. Harari, S., Miller, D., Fleishon, S. Burstein, D., &  Stern, A. (2024) Using big sequencing data to identify chronic SARS-Coronavirus-2 infections. Nat Commun 15, 648 (2024).


569. M. Eshel, B. Milon, R. Hertzano, R. Elkon (2024) The cells of the sensory epithelium, and not the stria vascularis, are the main cochlear cells related to the genetic pathogenesis of age-related hearing loss. Am J Hum Genet. 2024 Feb 2:S0002-9297(24)00008-9. 


568. Y. Hershko, E. Rannon, A. Adler, D. Burstein, D. Barkan (2024) WarA, a remote homolog of NpmA and KamB from Nocardia wallacei, confers broad spectrum aminoglycoside resistance in Nocardia and Mycobacteria. International Journal of Antimicrobial Agents,


567. Levinstein Hallak, K., Rosset, S. (2024) Dating ancient splits in phylogenetic trees, with application to the human-Neanderthal split. BMC Genomic Data, 25, 4 (2024),


566. C. Pascal*, J. Zonszain*, O. Hameiri, C. Gargi-Levi, G. Lev-Maor, L. Tammer, T. Levy, A. Tarabeih, V. R. Roy, S. Ben-Salmon, L. Elbaz, M. Eid, T. Hakim, S. Abu Rabe'a, N. Shalev, A. Jordan, E. Meshorer, G. Ast (2023) Human histone H1 variants impact splicing outcome by controlling RNA polymerase II elongationMolecular Cell, Volume 83, Issue 21, Pages 3801-3817.e8, * Equal contributors.


565. Abboud, M., Merenbakh-Lamin, K., Volkov, H. ...Shomron N. et al. (2023) Revealing the tumor suppressive sequence within KL1 domain of the hormone KlothoOncogene (2023).


564. Polonsky K, Pupko T, Freund NT. (2023) Evaluation of the Ability of AlphaFold to Predict the Three-Dimensional Structures of Antibodies and Epitopes. The Journal of Immunology. 2023 Nov 15;211(10):1578-88. 


563. Poppenwimer, T., Mayrose, I. & DeMalach, N. (2023) Revising the global biogeography of annual and perennial plants. Nature (2023),


562. G. Shapira, H. Volkov, I. Fabian, D. W. Mohr, M. Bettinotti, N. Shomron, R. K. Avery and R. Arav-Boger (2023) Genomic Markers Associated with Cytomegalovirus DNAemia in Kidney Transplant Recipients. Viruses 2023, 15(11), 2227; 


561. T. Mahata, S. Molshanski-Mor, M. G. Goren, M. Kohen-Manor, I. Yosef, O. Avram, D. Salomon, U. Qimron (2023) Inhibition of host cell division by T5 protein 008 (Hdi)Bacteriology, 27 October 2023, DOI:


560. D. Coster, A. Rafie, N. Savion, R. Rachmiel, S. Kurtz, S. Berliner, I. Shapira, D. Zeltser, O. Rogowski, S. Shenhar-Tsarfaty, M. Waisbourd (2023) "The Effect of Body Mass Index Reduction on Intraocular Pressure in a Large, Prospective Population-based Cohort Study in Israel". PLoS One,


559. E. Shpigelman, A. Hochstadt , D. Coster, I. Merdler, E. Ghantous, Y. Szekely, Y. Lichter, P. Taieb, A. Banai, O. Sapir, Y. Granot, L. Lupu, A. Borohovitz, S. Sadon, S. Banai, R. Rubinshtein, Y. Topilsky, R. Shamir (2023) "Clustering of Clinical-Echocardiographic Phenotypes of Covid-19 Disease Using Machine-Learning Techniques". Nature Scientific Reports,


558. Lee, B. D., Neri, U., Roux, S., Wolf, Y. I., Camargo, A. P., Krupovic, M., ... & Koonin, E. V. (2023) Mining metatranscriptomes reveals a vast world of viroid-like circular RNAs. Cell, 186(3), 646-661.


557. I. Israel-Elgali, H. Pan, K. Oved, N. Pillar, G. Levy, B. Barak, A. Carneiro, D. Gurwitz, N. Shomron (2023) Impaired myelin ultrastructure is reversed by citalopram treatment in a mouse model for major depressive disorderJournal of Psychiatric Research, 2023, ISSN 0022-3956,


556. Farberov L, Weissglas-Volkov D, Shapira G, Zoabi Y, Schiff C, Kloeckener-Gruissem B, Neidhardt J, Shomron N. (2023) mRNA splicing is modulated by intronic microRNAs. iScience. 2023 Aug 28;26(10):107723. doi: 10.1016/j.isci.2023.107723. PMID: 37692287; PMCID: PMC10492213.


555. I. Caspi, M. Meir, N. Ben Nun, R. Abu Rass, U. Yakhini, A. Stern, Y. Ram (2023) Mutation rate, selection, and epistasis inferred from RNA virus haplotypes via neural posterior estimation. Virus Evolution, Volume 9, Issue 1, 2023, vead033,


554. Moshe, A., Wygoda, E., Ecker, N., Loewenthal, G., Avram, O.,Israeli, O., Hazkani-Covo, E., Pe’er, I., & Pupko, T. (2022) An approximate Bayesian computation approach for modeling genome rearrangements. Molecular Biology and Evolution, 39(11), msac231.


553. G. Gilad and R. Sharan (2023) From Leiden to Tel-Aviv University (TAU): exploring clustering solutions via a genetic algorithm. PNAS Nexus, Volume 2, Issue 6, June 2023, pgad180,


552. Y. Pinto....E. Muller...E. Borenstein, O. Koren et al. (2023) Gestational diabetes is driven by microbiota-induced inflammation months before diagnosis. Gut, 2023;72:918–928. doi:10.1136/gutjnl-2022-328406.


551. C. T. Wei, N. A. Popp, O. Peleg, R.l L. Powell, E. Borenstein, D. J. Maly & D. M. Fowler (2023) A chemically controlled Cas9 switch enables temporal modulation of diverse effectorsNature Chemical Biology, volume 19, pages 981–991ת


550. Shapira G, Israel-Elgali I, Grad M, Avnat E, Rachmany L, Sarne Y, Shomron N (2023) Hippocampal differential expression underlying the neuroprotective effect of delta-9-tetrahydrocannabinol microdose on old mice. Front Neurosci. 2023 Jul 18;17:1182932. doi: 10.3389/fnins.2023.1182932. PMID: 37534036; PMCID: PMC10393280.


549. Miller, D., Stern, A. & Burstein, D. (2023) Deciphering microbial gene function using natural language processing. Nat Commun 13, 5731 (2022).


548. Yefet, R., N. Friedel, H. Tamir, K. Polonsky, M. Mor, L. Cherry-Mimran, E. Taleb, D. Hagin, E. Sprecher, T. Israely, and N. T. Freund (2023) Monkeypox infection elicits strong antibody and B cell response against A35R and H3L antigens. iScience 26: 105957.


547. K. Halabi, A. Shafir and I. Mayrose (2023) PloiDB: The plant ploidy database. New Phytologist (2023):


546. L. Glick, and I. Mayrose (2023) The effect of methodological considerations on the construction of gene-based plant pan-genomes. Genome Biology and Evolution (2023): evad121.


545. Dotan, E., Belinkov, Y., Avram, O., Wygoda, E., Ecker, N., Alburquerque, M., Keren, O., Loewenthal, G., and Pupko, T. (2023) Multiple sequence alignment as a sequence-to-sequence learning problem. The Eleventh International Conference on Learning Representations (ICLR 2023).


544. Dotan, E., Alburquerque, M., Wygoda, E., Huchon, D., and Pupko, T. (2023) GenomeFLTR: filtering reads made easy. Nucleic Acids Research: 51(Web Server issue):W232-W236.


543. R. Nasser and R. Sharan (2023) BERTwalk for integrating gene networks to predict gene- to pathway-level properties. Bioinformatics Advances, Volume 3, Issue 1, 2023, vbad086,


542. H. Levi, S. Carmi, S. Rosset, R. Yerushalmi, A. Zick, T. Yablonski-Peretz, .... (127 members of the BCAC Consortium)..., S. Ben-Shachar, N. Elefant*, R. Shamir* and R. Elkon* (2023) Evaluation of European-based polygenic risk score for breast cancer on Ashkenazi Jewish women. Journal of Medical Genetics doi:10.1136/jmg-2023-109185 (2023).


541. M. Arbel-Groissman, I. Menuhin-Gruman, D. Naki, S. Bergman, T. Tuller (2023) Fighting the battle against evolution: designing genetically modified organisms for evolutionary stabilityTrends in Biotechnology, ISSN 0167-7799,


540. S. Kumari, A. Kessel, D. Singhal, G. Kaur, D. Bern, C. Lemay-St-Denis, J. Singh & S. Jain (2023) Computational identification of a multi-peptide vaccine candidate in E2 glycoprotein against diverse Hepatitis C virus genotypesJournal of Biomolecular Structure and Dynamics,


539. Algavi, Y.M., Borenstein, E. (2023) A data-driven approach for predicting the impact of drugs on the human microbiome. Nat Commun 14, 3614 (2023).


538. N. Wagner, D. Ben-Meir, D. Teper and T. Pupko (2023) Complete genome sequence of an Israeli isolate of Xanthomonas hortorum pv. pelargonii strain 305 and novel type III effectors identified in XanthomonasFront. Plant Sci., Volume 14 - 2023.


537. G. Simchoni, S. Rosset (2023) Integrating Random Effects in Deep Neural Networks. Journal of Machine Learning Research 24(156):1−57, 2023.


536. P. Ofek, E. Yeini, G. Arad, A. Danilevsky, S. Pozzi, C. Burgos Luna, S. Israeli Dangoor, R. Grossman, Z Ram, N. Shomron, H. Brem, T. M. Hyde, T. Geiger, R. Satchi-Fainaro (2023)  Deoxyhypusine hydroxylase: A novel therapeutic target differentially expressed in short-term vs long-term survivors of glioblastoma. Int J Cancer. 2023;1‐15. doi:10.1002/ijc.34545.


535. Y. Hu, P. Patra, O. Pisanty, A. Shafir, Z. M. Belew, J. Binenbaum, S. Ben Yaakov, B. Shi, L. Charrier, G. Hyams, Y. Zhang, M. Trabulsky, O. Caldararu, D. Weiss, C. Crocoll, A. Avni, T. Vernoux, M. Geisler, H. Hassan Nour-Eldin, I. Mayrose & E. Shani (2023). Multi-Knock—a multi-targeted genome-scale CRISPR toolbox to overcome functional redundancy in plants. Nat. Plants 9, 572–587 (2023).


534. Avnat E, Shapira G, Shoval S, Israel-Elgali I, Alkelai A, Shuldiner AR, Gonzaga-Jauregui C, Zidan J, Maray T, Shomron N, Friedman E. Comprehensive Genetic Analysis of Druze Provides Insights into Carrier Screening. Genes (Basel). 2023 Apr 18;14(4):937. doi: 10.3390/genes14040937. 


533. A. Shafir, K. Halabi, M. Escudero and I. Mayrose (2023) A non-homogeneous model of chromosome-number evolution to reveal shifts in the transition patterns across the phylogeny.  New Phytologist, 2023


532. G. Shapira, T. Patalon, S. Gazit and N. Shomron (2023) Immunosuppression as a Hub for SARS-CoV-2 Mutational Drift. Viruses, 2023, 15(4), 855;


531. B. Pertzov, G. Shapira, S. Abushkara, S. Cohen, A. Turjeman, M. R. Kramer, D. Gurwitz & N. Shomron (2022) Lower serum alpha 1 antitrypsin levels in patients with severe COVID-19 compared with patients hospitalized due to non-COVID-19 pneumonia. Infectious Diseases, Pages 846-851,


530.  L. Farberov, A. Ionescu, Y. Zoabi, G. Shapira, A. Ibraheem, Y. Azan, E. Perlson and N. Shomron (2023) Multiple Copies of microRNA Binding Sites in Long 3′UTR Variants Regulate Axonal Translation. Cells 2023, 12(2), 233;

529. E. Levert-Levitt, G. Shapira, S. Sragovich, N. Shomron, M. M. Heimesaat, S. Bereswill, A. Ben Yehuda, A. Sagi-Schwartz, Z. Solomon and I. Gozes (2022) Oral microbiota signatures in post-traumatic stress disorder (PTSD) veterans. Molecular Psychiatry (2022) 27:4590–4598; 


528. A. Gutwillig, N Santana-Magal, L. Farhat-Younis, D. Rasoulouniriana, A.Madi, C. Luxenburg, J. Cohen, K. Padmanabhan, N. Shomron, G. Shapira, A. Gleiberman, R. Parikh, C. Levy, M. Feinmesser , D. Hershkovitz, V. Zemser-Werner, O. Zlotnik, S. Kroon, W.-D. Hardt, R. Debets (2022) Transient cell-in-cell formation underlies tumor relapse and resistance to immunotherapy. ELife. , 2022, Vol.11, p.e80315; DOI: 10.7554/eLife.80315.


527. L. Admoni-Elisha, T. Elbaz, A. Chopra, G. Shapira, M. T Bedford, C. J Fry, N. Shomron, K. Biggar, M. Feldman, D. Levy (2022) TWIST1 methylation by SETD6 selectively antagonizes LINC-PINT expression in glioma. Nucleic Acids Research, Volume 50, Issue 12, 8 July 2022, Pages 6903–6918,


526. L. Kuznitsov-Yanovsky, G. Shapira, L. Gildin, N. Shomron and D. Ben-Yosef (2022) Transcriptomic Analysis of Human Fragile X Syndrome Neurons Reveals Neurite Outgrowth Modulation by the TGFβ/BMP Pathway. Int. J. Mol. Sci. 2022, 23(16), 9278;


525. M. Cohen-Gulkar, A. David, N. Messika-GoldM. Eshel, S. Ovadia, N. Zuk-Bar, M. Idelson, Y. Cohen-Tayar, B. Reubinoff, T. Ziv, M. Shamay, R. Elkon, R. Ashery-Padan (2023) The LHX2-OTX2 transcriptional regulatory module controls retinal pigmented epithelium differentiation and underlies genetic risk for age-related macular degeneration. PloS Biology,


524. Panda, A., Tuller, T. (2023) Determinants of associations between codon and amino acid usage patterns of microbial communities and the environment inferred based on a cross-biome metagenomic analysis. npj Biofilms Microbiomes 9, 5 (2023).


523. Hen Gabzi R, Patalon T, Shomron N, Gazit S (2022) A Data-Driven Strategy for Identifying Individuals Resistant to SARS-CoV-2 Virus under In-Household Exposure. J Pers Med. 30;12(12):1975. doi: 10.3390/jpm12121975. 


522. M. Kilian, R. Sheinin, C. Leng Tan, M. Friedrich, C. Krämer, A. Kaminitz, K. Sanghvi, K. Lindner, Y.C. Chih, F. Cichon, B. Richter, S. Jung, K. Jähne, M. Ratliff, R. M. Prins, N. Etminan, A. von Deimling, W. Wick, A. Madi, L. Bunse, M. Platten (2023) MHC class II-restricted antigen presentation is required to prevent dysfunction of cytotoxic T cells by blood-borne myeloids in brain tumors. Cancer Cell,


521. Neri U, Wolf YI, Roux S, Camargo AP, Lee B, Kazlauskas D, Chen IM, Ivanova N, Zeigler Allen L, Paez-Espino D, Bryant DA, Bhaya D; RNA Virus Discovery Consortium, Krupovic M, Dolja VV, Kyrpides NC, Koonin EV, Gophna U (2022) Expansion of the global RNA virome reveals diverse clades of bacteriophages. Cell. 2022 Sep 25:S0092-8674(22)01118-7. doi: 10.1016/j.cell.2022.08.023. PMID: 36174579.


520. Loewenthal G., Wygoda E., Nagar N., Glick L., Mayrose I. and Pupko T. (2022) The evolutionary dynamics that retain long neutral genomic sequences in face of indel deletion bias: a model and its application to human introns. Open Biol.12220223220223


519. Armoni R, Borenstein E. (2022) Temporal Alignment of Longitudinal Microbiome Data. Front Microbiol. 2022 Jun 22;13:909313. doi: 10.3389/fmicb.2022.909313. 


518. G. M. Douglas, M. G. Hayes, M. G. I. Langille, E. Borenstein (2022) Integrating phylogenetic and functional data in microbiome studies. Bioinformatics, Volume 38, Issue 22,  Pages 5055–5063,


517. Muller, E., Algavi, Y.M. & Borenstein, E. (2022) The gut microbiome-metabolome dataset collection: a curated resource for integrative meta-analysisnpj Biofilms Microbiomes 8, 79 (2022).


516. Y. Cohen,  E. Borenstein (2022) The microbiome’s fiber degradation profile and its relationship with the host diet. BMC Biol 20, 266 (2022).


515. Abu Rass R, Kustin T, Zamostiano R, Smorodinsky N, Ben Meir D, Feder D, Mishra N, Lipkin WI, Eldar A, Ehrlich M, Stern A, Bacharach E (2022) Inferring Protein Function in an Emerging Virus: Detection of the Nucleoprotein in Tilapia Lake Virus. J Virol. ;96(6):e0175721. doi: 10.1128/JVI.01757-21. 


514.  A. Dutta, D. Pellow, R. Shamir (2022) Parameterized syncmer schemes improve long-read mapping (2022) PLOS Comp Bio,

513. O. Shelef*, S. Gutkin*, D. Feder*, A. Ben-Bassat, M. Mandelboim, Y. Haitin, N. Ben-Tal, E. Bacharach, and D. Shabat (2022) Ultrasensitive chemiluminescent neuraminidase probe for rapid screening and identification of small-molecules with antiviral activity against influenza A virus in mammalian cellsChem Sci.  13(42): 12348–12357, doi: 10.1039/d2sc03460c. * Equal contributors.


512. D. Feder, S. H. Mohd-Pahmi, W. M. Hussein, L. W. Guddat, R. P. McGeary, G. Schenk (2021) Rational Design of Potent Inhibitors of a Metallohydrolase Using a Fragment-Based ApproachChemMedChem,


511. N. Wagner, M. Alburquerque, N. Ecker, E. Dotan, B. Zerah, M. Mendonca Pena, N. Potnis and T. Pupko (2022) Natural language processing approach to model the secretion signal of type III effectorsFront. Plant Sci., Sec. Plant Systems and Synthetic Biology,


510. Azouri, D., Abadi, S., Mansour, Y., Mayrose, I., and Pupko, T. (2021) Harnessing machine learning to guide phylogenetic-tree search algorithms. Nature Communications. 12:1983.


509. Mayer O, Bugis J, Kozlova D, Leemann A, Mansur S, Peerutin I, Mendelovich N, Mazin M, Friedmann-Morvinski D, Shomron N (2022) Cytoskeletal Protein Palladin in Adult Gliomas Predicts Disease Incidence, Progression, and Prognosis. Cancers (Basel). 19;14(20):5130. doi: 10.3390/cancers14205130.


508. Wendao Liu  N. Shomron (2022) Analysis of MicroRNA Regulation and Gene Expression Variability in Single Cell Data. J. Pers. Med. 2022, 12(10), 1750;


507. E. Avnat, G. Shapira, D. Gurwitz, N. Shomron (2022) Elevated Expression of RGS2 May Underlie Reduced Olfaction in COVID-19 Patients. J. Pers. Med. 2022, 12, 1396.


506. I. Voinsky, Y. Zoabi, N. Shomron, M. Harel, H. Cassuto, J. Tam, S. Rose, A. C. Scheck, M. A. Karim, R. E. Frye, A. Aran  and D. Gurwitz (2022) Blood RNA Sequencing Indicates Upregulated BATF2 and LY6E and Downregulated ISG15 and MT2A Expression in Children with Autism Spectrum Disorder. Int. J. Mol. Sci. 2022, 23(17), 9843;


505. A. David Nahmad*,  E. Reuveni*, E. Goldschmidt*, T. Tenne, M. Liberman, M. Horovitz-Fried, R. Khosravi, H. Kobo, E. Reinstein, A. Madi, U. Ben-David & A. Barzel (2022) Frequent aneuploidy in primary human T cells after CRISPR–Cas9 cleavage
Nature Biotechnology, *equal contribution.


504. L. Chitayat Levi, I. Rippin, M. Ben Tulila, R. Galron and T. Tuller (2022) Modulating Gene Expression within a Microbiome Based on Computational Models. Biology 2022, 11(9), 1301;


503. N. Ecker, D. Azouri, B. Bettisworth, A. Stamatakis, Y. Mansour, I. Mayrose, T. Pupko (2022) A LASSO-based approach to sample sites for phylogenetic tree searchBioinformatics, Volume 38, Issue Supplement_1, July 2022, Pages i118–i124,


502. E. Avnat*, G. Shapira*, D. Gurwitz and N. Shomron (2022) Elevated Expression of RGS2 May Underlie Reduced Olfaction in COVID-19 Patients. J. Pers. Med. 2022, 12(9), 1396;

*These authors contributed equally to this work.


501. A. Danilevsky, A. Luba Polsky, N. Shomron (2022) Adaptive sequencing using nanopores and deep learning of mitochondrial DNA. Briefings in Bioinformatics, Volume 23, Issue 4, July 2022, bbac251,

500. N. Wagner, D. Teper & T. Pupko (2022) Predicting Type III Effector Proteins Using the Effectidor Web Server. In: Gal-Mor, O. (eds) Bacterial Virulence. Part of the Methods in Molecular Biology book series (MIMB,volume 2427).

499. J. Tubiana,  D. Schneidman-Duhovny & H. J. Wolfson (2022) ScanNet: An interpretable geometric deep learning model for structure-based protein binding site prediction. Nature Methods, 19, 730–739.


498. S. Harari,  M. Tahor,  N. Rutsinsky, S. Meijer, D. Miller, O. Henig, O. Halutz, K. Levytskyi, R. Ben-Ami, A. Adler, Y. Paran & A. Stern (2022)  Drivers of adaptive evolution during chronic SARS-CoV-2 infections. Nature Med,

497. L. Admoni-Elisha, E. Abaev-Schneiderman, O. Cohn, G. Shapira, N. Shomron, M. Feldman, D. Levy (2022) Structure-function conservation between the methyltransferases SETD3 and SETD6. Biochimie, Vol 200, Pages 27-35,

496. M. Grad, A. Nir, G. Levy, S. Schokoroy Trangle, G. Shapira, N. Shomron,Y. Assaf, B. Barak (2022) Altered White Matter and microRNA Expression in a Murine Model Related to Williams Syndrome Suggests That miR-34b/c Affects Brain Development via Ptpru and Dcx Modulation. Cells, DOI: 10.3390/cells11010158,  2022, Vol.11(1), p.158.

495. D. Sheinboim, S. Parikh, R. Parikh, A. Menuchin, G. Shapira, O. Kapitansky, N. Elkoshi, S. Ruppo, L. Shaham, T. Golan, S. Elgavish, Y. Nevo, R. E. Bell, H. Malcov-Brog, N. Shomron, J. W. Taub, S. Izraeli, C. Levy (2022) Slow Transcription of the 99a/let-7c/125b-2 Cluster Results in Differential MiRNA Expression and Promotes Melanoma Phenotypic PlasticityJournal of Investigative Dermatology, Vol 141, Issue 12, 2021, Pages 2944-2956.e6,


494. A. Dolitzky, G. Shapira, S. Grisaru-Tal, I. Hazut, S. Avlas, Y. Gordon, M. Itan, N. Shomron and A. Munitz (2021) Transcriptional Profiling of Mouse Eosinophils Identifies Distinct Gene Signatures Following Cellular ActivationFront. Immunol., 


493. G. Shapira, R. Abu Hamad, C. Weiner, N. Rainy, R. Sorek-Abramovich, P. Benveniste-Levkovitz, R. Rock, E. Avnat, O. Levtzion-Korach, A. Bar Chaim, N. Shomron (2022) Population differences in antibody response to SARS-CoV-2 infection and BNT162b2 vaccination. FASEB Journal,


492. G. Karmon, S. Sragovich, G. Hacohen-Kleiman, I. Ben-Horin-Hazak, P. Kasparek, B. Schuster, R. Sedlacek, M. Pasmanik-Chor, P. Theotokis, O. Touloumi, S. Zoidou, L. Huang, P. You Wu, R. Shi, O. Kapitansky, A. Lobyntseva, E. Giladi, G. Shapira, N. Shomron, S. Bereswill, M. M. Heimesaat, N. Grigoriadis, R. A. McKinney, M. Rubinstein, and I. Gozes (2021) Novel ADNP Syndrome Mice Reveal Dramatic Sex-Specific Peripheral Gene Expression With Brain Synaptic and Tau PathologiesBiological psychiatry a journal of psychiatric research , DOI: 10.1016/j.biopsych.2021.09.018.


491. S. Labes, D. Stupp, N. Wagner, I. Bloch, M. Lotem, E. L. Lahad, P. Polak, T. Pupko, Y. Tabach (2022) Machine-learning of complex evolutionary signals improves classification of SNVs. NAR Genomics and Bioinformatics, Volume 4, Issue 2, June 2022, lqac025,


490. M. Levine-Tiefenbrun, I. Yelin, H. Alapi, E. Herzel, J. Kuint, G. Chodick, S. Gazit, T. Patalon & R. Kishony (2022) Waning of SARS-CoV-2 booster viral-load reduction effectiveness. Nature Communications, volume 13, Article number: 1237 (2022).


489. M. Sharon, E. Vinogradov, C. M. Argov, O. Lazarescu, Y. Zoabi, I. Hekselman, E. Yeger-Lotem (2022) The differential activity of biological processes in tissues and cell subsets can illuminate disease-related processes and cell-type identities. Bioinformatics, Volume 38, Issue 6, 15 March 2022, Pages 1584–1592,


488. D. Flomin, D. Pellow, and R. Shamir (2022) Data Set-Adaptive Minimizer Order Reduces Memory Usage in k-Mer Counting. Journal of Computational Biology,


487. Baum, I.  Atar,  D. Coster,  S. Dovrat,  M. Solomon,  E. Sprecher,  T. Zeeli  and  A. Barzilai (2022) Relationship Between Pemphigus Vulgaris Severity and PCR-positive Herpes Simplex VirusActaDV, Vol. 102 (2022), DOI:


486. G. Simchoni and S. Rosset (2022) Using Random Effects to Account for High-Cardinality Categorical Features and Repeated Measures in Deep Neural Networks.  Part of Advances in Neural Information Processing Systems 34 (NeurIPS 2021) .


485. P. Liyanapathiranage, N. Wagner, O. Avram, T. Pupko and N. Potnis (2022) Phylogenetic Distribution and Evolution of Type VI Secretion System in the Genus Xanthomonas. Front. Microbiol.,


484. D. Groenewoud, A. Shye, R. Elkon (2022) Incorporating regulatory interactions into gene-set analyses for GWAS data: A controlled analysis with the MAGMA tool. PLoS Comp Bio.


483. I. Menuhin-Gruman, M. Arbel, N. Amitay, K. Sionov, D. Naki, I. Katzir, O. Edgar, S. Bergman, and T. Tuller (2022) Evolutionary Stability Optimizer (ESO): A Novel Approach to Identify and Avoid Mutational Hotspots in DNA Sequences While Maintaining High Expression Levels.  ACS Synth. Biol. 2022, 11, 3, 1142–1151,


482. L. Tammer, O. Hameiri, I. Keydar, V. R. Roy,  A. Ashkenazy-Titelman, N. Custodio, I. Sason, R. Shayevitch, V. Rodrguez-Vaello, J. Rino, G. Lev Maor, Yodfat. Leader, D. Khair, E. Lieberman Aiden, R. Elkon, M. Irimia, R. Sharan, Y. Shav-Tal, Maria. Carmo-Fonseca and G. Ast (2022) Gene architecture directs splicing outcome in separate nuclear spatial regions. Molecular Cell,


481. N. Nagar, N. Ben-Tal, T. Pupko (2022) EvoRator: Prediction of residue-level evolutionary rates from protein structures using machine learning. jmb,


480. N. Wagner, O. Avram, D. Gold-Binshtok, B. Zerah, D. Teper, T. Pupko (2022) Effectidor: an automated machine-learning-based web server for the prediction of type-III secretion system effectors. Bioinformatics, btac087,


479. O. Noy*, D. Coster*, M. Metzger, I. Attar, S. Shenhar-Tsafraty, S. Berliner, G. Rahav, O.Rogowski, R. Shamir (2022) A machine learning model for predicting deterioration of COVID-19 inpatients. Nature Scientific Reports Article 2630 DOI 10.1038/s41598-022-05822-7 (2022).


478. H. Levi, N. Rahmanian, R. Elkon, R. Shamir (2022) The DOMINO web-server for active module identification analysis. Bioinformatics, btac067,


477. T. A. Hait, R. Elkon, R. Shamir (2022) CT-FOCS: a novel method for inferring cell type-specific enhancer-promoter maps. Nucleic Acids Research, gkac048, (2022).


476. G. Gilad, I. Sason and R. Sharan (2021) An automated approach for determining the number of components in non-negative matrix factorization with application to mutational signature learning (2021) Machine Learning: Science and Technology, Volume 2, Number 1, 015013.


475. Nahmad, A.D., Lazzarotto, C., Zelikson, N., Kustin, T., Tenuta, M., Huang, D., Reuveni, I., Horovitz-Fried, M., Dotan, I., Rosin-Arbesfeld, R. and Nemazee, D., 2021. In-vivo engineering of B cells elicits memory retention and allows for secretion of broadly neutralizing antibodies in mice. J Immunol 2021, 206 (1 Supplement) 59.14.


474. R. Shouval*, A. Eshel*, B. Dubovski, Am. A. Kuperman, I. Danylesko, J. A. Fein, S. Fried, M. Geva, E. Kouniavski, H. Neuman, A. Armon-Omer, R. Shahien, E. Muller, C. Noecker, E. Borenstein, Y. Louzoun, A. Nagler, and O. Koren (2021) Patterns of salivary microbiota injury and oral mucositis in recipients of allogeneic hematopoietic stem cell transplantationBlood advances, 4.13 (2020): 2912-2917.


473. MR. Goldberg, H. Mor, DM Neriya, F. Magzal, E. Muller, MY Appel, L. Nachshon, E. Borenstein, S. Tamir, Y. Louzoun, I. Youngster, A. Elizur and O. Koren (2021) Microbial signature in IgE-mediated food allergies. Genome Medicine. 2020 Dec;12(1):1-8.


472. E. Muller, Y.M. Algavi, and E. Borenstein (2021) A meta-analysis study of the robustness and universality of gut microbiome-metabolome associations. Microbiome, 9.1 (2021): 1-18.


471. Lee, B. D., Neri, U., Oh, C. J., Simmonds, P., & Koonin, E. V. (2021) ViroidDB: a database of viroids and viroid-like circular RNAsNucleic Acids Research. Volume 50, Issue D1, Pages D432–D438,


470. S. Bahiri Elitzur, R. Cohen-Kupiec, D. Yacobi, L. Fine, B. Apt, A. Diament & T. Tuller (2021) Prokaryotic rRNA-mRNA interactions are involved in all translation steps and shape bacterial transcriptsRNA Biology, Pages 684-698 | Published online: 29 Sep 2021,


469. I. Israel-Elgali, L. Hertzberg, G. Shapira, A. Segev, I. Krieger, U. Nitzan, Y. Bloch, N. Pillar, O. Mayer, A. Weizman, D. Gurwitz, N. Shomron (2021) Blood transcriptional response to treatment-resistant depression during electroconvulsive therapyJournal of Psychiatric Research, Volume 141, 2021, Pages 92-103, ISSN 0022-3956,


468. D. Bernstein, D. Coster, S. Berliner, I. Shapira, D. Zeltser, O. Rogowski, A. Adler, O. Halutz, T. Levinson, O. Ritter, S. Shenhar-Tsarfaty & A. Wasserman (2021) C-reactive protein velocity discriminates between acute viral and bacterial infections in patients who present with relatively low CRP concentrations. BMC Infect Dis 21, 1210 (2021).


467. A. Dorchin, A. Shafir, F. H. Neumann, D. Langgut, N. J. Vereecken and I. Mayrose (2021) Bee flowers drive macroevolutionary diversification in long-horned bees. Proc. R. Soc. B Biol. Sci. 288, 307–326 (2021).,


466. K. E. Shapira, G. Shapira, E. Schmukler, M. Pasmanik-Chor, N. Shomron, R. Pinkas-Kramarski, Y. I. Henis and M. Ehrlich (2021) Autophagy is induced and modulated by cholesterol depletion through transcription of autophagy-related genes and attenuation of flux. Cell Death Discovery (2021) 7:320 ;


465. T.S. Menes,  D. Coster,  and S. Shenhar-Tsarfaty (2021). Contribution of clinical breast exam to cancer detection in women participating in a modern screening programBMC Women's Health, 21(1) 368, pp.1-8.,


464. Y. Zoabi, O. Kehat, D. Lahav, A. Weiss-Meilik, A. Adler & N. Shomron (2021) Predicting bloodstream infection outcome using machine learning. Scientific Reports, volume 11, Article number: 20101 (2021), 


463. B. Milon*, E. D. Shulman*, K. S. So, C. R. Cederroth, E. L. Lipford, M. Sperber, J. B. Sellon, H. Sarlus, G. Pregernig, B. Shuster, Y. Song, S. Mitra, J. Orvis, Z. Margulies, Y. Ogawa, C. Shults, D. A. Depireux, A. T. Palermo, B. Canlon, J. Burns, R. Elkon*, R. Hertzano* (2021). A cell-type-specific atlas of the inner ear transcriptional response to acoustic trauma. Cell Reports, 2021; 36 (13): 109758. 


462.  G. Loewenthal, D. Rapoport, O. Avram, A. Moshe, E. Wygoda, A. Itzkovitch, O. Israeli, D. Azouri, R. A. Cartwright, I. Mayrose and T. Pupko (2021) A probabilistic model for indel evolution: differentiating insertions from deletions. Molecular Biology and Evolution, msab266, 


461. A. Catav, B. Fu, Y.  Zoabi, A. Weiss-Meilik, N. Shomron, J. Ernst, S. Sankararaman, R. Gilad-Bachrach. Marginal Contribution Feature Importance - an Axiomatic Approach for Explaining Data. Proceedings of the 38th International Conference on Machine Learning, PMLR, 139:1324-1335, 2021., July 2021,


460.  A. Schupper,  S. Almashanu, D. Coster, R. Keidar, M. Betser, N. Sagiv and H. Bassan (2021). Metabolic biomarkers of small and large for gestational age newborns. Early Human Development, Volume 160, 105422, ISSN 0378-3782,


459. Y. Ben-Ari, D. Flomin, L. Pu, Y. Orenstein, R. Shamir (2021) Improving the efficiency of de Bruijn graph construction using compact universal hitting sets. Proc. ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB), August 2021, Article No.: 4, pp 1–9,


458. S. Belaish,  I. Israel-Elgali,  G. Shapira,  I. Krieger, A. Segev, U. Nitzan, M. Majer, Y. Bloch, A. Weizman, D. Gurwitz, N. Shomron & L. Hertzberg (2021) Genome wide analysis implicates upregulation of proteasome pathway in major depressive disorder. Transl Psychiatry 11, 409 (2021).


457. D. Pellow, M. Probst, O. Furman, A. Zorea, A. Segal, I. Mizrahi, R. Shamir (2021) SCAPP: An algorithm for improved plasmid assembly in metagenomes. Microbiome 9, 144 (2021),


456. E. D. Shulman and R. Elkon (2021) Genetic mapping of developmental trajectories for complex traits and diseases. Computational and Structural Biotechnology Journal, Volume 19, 2021, Pages 3458-3469.


455. T. Kustin, N. Harel, U. Finkel, S. Perchik, S. Harari.........A. Stern (2021) Evidence for increased breakthrough rates of SARS-CoV-2 variants of concern in BNT162b2-mRNA-vaccinated individuals. Nature Medecine (2021),


454. A. Panda, T. Tuller (2020) Exploring Potential Signals of Selection for Disordered Residues in Prokaryotic and Eukaryotic Proteins. Genomics, Proteomics & Bioinformatics, 2020, ISSN 1672-0229,


453. T. Mahata, S. Molshanski-Mor,  M. G. Goren, B. Jana,  M. Kohen-Manor,  I. Yosef,  O. Avram,  T. Pupko,  D. Salomon, and  U. Qimron (2021) A phage mechanism for selective nicking of dUMP-containing DNA. PNAS June 8, 2021 118 (23) e2026354118;


452. K. Halabi, I. Mayrose (2021) Mechanisms Underlying Host Range Variation in Flavivirus: From Empirical Knowledge to Predictive Models. J Mol Evol (2021).


451.  H.  Ashkenazy*O.  Avram*,  A.  Ryvkin*,  A.  Roitburd-Berman,  Y.  Weiss-Ottolenghi,  S.Hada-Neeman,  J.M.  Gershoni,  T.  Pupko (2021) Motifier:  an  IgOme  profiler  based  on  peptide-motifs  using  machine learningJournal of Molecular Biology (2021), doi:  *equally contributed.


450. G. Yankovitz , O. Cohn , E. Bacharach, N. Peshes-Yaloz , Y. Steuerman, F.A. Iraqi, I. Gat-Viks (2021) Leveraging the cell lineage to predict cell-type specificity of regulatory variation from bulk genomics. Genetics, 15;217(4):iyab016. doi: 10.1093/genetics/iyab016. PMID: 33734353; PMCID: PMC8049554.


449. K. Halabi, E. Levy Karin, L. Guéguen, I. Mayrose (2021) A Codon Model for Associating Phenotypic Traits with Altered Selective Patterns of Sequence Evolution. Systematic Biology, Volume 70, Issue 3, Pages 608–622,


448. L. Glick and I. Mayrose (2021) Panoramic: A package for constructing eukaryotic pan‐genomes. Molecular Ecology Resources,


447. G. Loewenthal*,  S. Abadi*,  O. Avram*,  K. Halabi*,  N. Ecker*,  N. Nagar, I. Mayrose, T. Pupko (2020) COVID‐19 pandemic‐related lockdown: response time is more important than its strictness. EMBO Mol Med (2020)12:e13171 *equally contributed.

446. S. Abadi, O. Avram, S. Rosset, T. Pupko, I. Mayrose (2020) ModelTeller: Model Selection for Optimal Phylogenetic Reconstruction Using Machine Learning. Molecular Biology and Evolution, Volume 37, Issue 11, Pages 3338–3352,

445. S. Bahiri-Elitzur, T. Tuller (2021) Codon-based indices for modeling gene expression and transcript evolution. Computational and Structural Biotechnology Journal, Volume 19, 2021, Pages 2646-2663,


444. D. Ruano-Gallego, J. Sanchez-Garrido, Z. Kozik, E. Núñez-Berrueco,  M. Cepeda-Molero,  C. Mullineaux-Sanders,  J. Naemi-Baghshomali Clark,  Sabrina L. Slater,  N. Wagner,  I. Glegola-Madejska,  T. I. Roumeliotis, T. Pupko, l. Ángel Fernández,  A. Rodríguez-Patón,  J. S. Choudhary,  G. Frankel (2021) Type III secretion system effectors form robust and flexible intracellular virulence networks. Science, Vol. 371, Issue 6534, eabc9531, DOI: 10.1126/science.abc9531.


443. D. Miller,  M.A. Martin,  N. Harel,  O. Tirosh, T. Kustin, A. Stern et al. (2020) Full genome viral sequences inform patterns of SARS-CoV-2 spread into and within Israel. Nat Commun 11, 5518 (2020).


442. V. Dubinsky, L. Reshef, K. Rabinowitz, K. Yadgar, L. Godny, K. Zonensain, N. Wasserberg, I. Dotan, U. Gophna. (2021) Dysbiosis in metabolic genes of the gut microbiomes of patients with an ileo-anal pouch resembles that observed in Crohn's disease. mSystems 6:e00984-20.


441.  D. Netanely, S. Leibou, R. Parikh, N. Stern, H. Vaknine, R. Brenner, S. Amar, R. Haiat Factor, T. Perluk, J. Frand, E Nizri, D. Hershkovitz, V. Zemser-Werner, C. Levy, R. Shamir (2021) Classification of node-positive melanomas into prognostic subgroups using keratin, immune and melanogenesis expression patterns. Oncogene (2021).


440. S. Hada-Neeman, Y. Weiss-Ottolenghi,  N. Wagner, O. Avram, H. Ashkenazy, Y. Maor,  E. H. Sklan, D. Shcherbakov, T. Pupko and J. M. Gershoni (2021) Domain-Scan: Combinatorial Sero-Diagnosis of Infectious Diseases Using Machine Learning. Front. Immunol., 10 February 2021,


439. O. Avram, A. Kigel,  A. Vaisman-Mentesh, S. Kligsberg, S. Rosenstein, Y. Dror, T. Pupko, Y. Wine (2021) PASA: Proteomic analysis of serum antibodies web server. PLoS Computational Biology,


438.  N. Nagar, N. Ecker, G. Loewenthal, O. Avram, D. Ben-Meir, D. Biran, E. Ron, T. Pupko (2021) Harnessing Machine Learning To Unravel Protein Degradation in Escherichia coli. mSystems, DOI: 10.1128/mSystems.01296-20.


437. H. Levi, R. Elkon, R. Shamir (2021) "DOMINO - a novel network-based active module identification algorithm with reduced rate of false calls". Molecular Systems Biology 17:e9593 (2021).


436. T. Rabinowitz, S. Deri-Rozov, N. Shomron (2021) Improved noninvasive fetal variant calling using standardized benchmarking approaches. Computational and Structural Biotechnology Journal , 19 (2021) 509–517.


435. Y. Zoabi, S. Deri-Rozov and Noam Shomron (2021) Machine learning-based prediction of COVID-19 diagnosis based on symptoms. npj Digital Medicine, 4:3,


434. S. Bergman, A. Diament, T. Tuller (2020) New computational model for miRNA-mediated repression reveals novel regulatory roles of miRNA bindings inside the coding region. Bioinformatics, btaa1021,


433. M. Meir, N. Harel, D. Miller, M. Gelbart, A. Eldar, U. Gophna* and A. Stern* (2020) Competition between social cheater viruses is driven by mechanistically different cheating strategies. Science Advances  21 Aug 2020: Vol. 6, no. 34, eabb7990, DOI: 10.1126/sciadv.abb7990.


432. M. Gelbart and A. Stern (2020) Site-Specific Evolutionary Rate Shifts in HIV-1 and SIV. Viruses 2020, 12(11), 1312;


431. M. Gelbart ,S. Harari ,Y. Ben-Ari, T. Kustin, D. Wolf, M. Mandelboim, O. Mor, P. S. Pennings, A. Stern (2020) Drivers of within-host genetic diversity in acute infections of viruses. PLOS Pathogens, Published: November 4, 2020 


430. A. Uzan-Yulzari, M. Morr, H. Tareef-Nabwani, O. Ziv, D. Magid-Neriya, R. Armoni, E. Muller, A. Leibovici, E. Borenstein, Y. Louzoun, A. Shai & O. Koren (2020) The intestinal microbiome, weight, and metabolic changes in women treated by adjuvant chemotherapy for breast and gynecological malignancies. BMC Medicine volume 18, Article number: 281 (2020). 


429. T. Kustin and A. Stern (2020) Biased mutation and selection in RNA viruses. Molecular Biology and Evolution, msaa247,


428. N. Rappoport, R. Safra, R. Shamir (2020) MONET: Multi-omic patient module detection by omic selection. PLoS Computational Biology 16 (9) e1008182 (2020).


427. Y. Chemla, M. Peeri, M. L. Heltberg, J. Eichler, M. H. Jensen, T. Tuller & L. Alfonta (2020) A possible universal role for mRNA secondary structure in bacterial translation revealed using a synthetic operon.  Nat Commun 11, 4827 (2020).


426. A. N. Gale, R. M. Sakhawala, A. Levitan, R. Sharan, J. Berman, W. Timp and K. W. Cunningham (2020) Identification of Essential Genes and Fluconazole Susceptibility Genes in Candida glabrata by Profiling Hermes Transposon Insertions. G3: Genes, Genomes, Genetics, August 20, 2020;


425. E. D. Shulman, R. Elkon, Systematic identification of functional SNPs interrupting 3’ UTR polyadenylation signals, PLOS Genetics, August 17, 2020,


424. A. Levitan, A. N. Gale, E. K. Dallon, D. W. Kozan, K. W. Cunningham, R. Sharan & J. Berman (2020) A Comparing the utility of in vivo transposon mutagenesis approaches in yeast species to infer gene essentiality. Curr Genet (2020).


423. R. Rabinowitz, S. Abadi, S. Almog, D. Offen (2020) Prediction of synonymous corrections by the BE-FF computational tool expands the targeting scope of base editing. Nucleic Acids Research, Volume 48, Issue W1, 02 July 2020, Pages W340–W347,


422. L. B. Harrington, E. Ma, J. S. Chen, I. P. Witte, D. Gertz, D. Paez-Espino,  B. Al-Shayeb, N. C. Kyrpides, D. Burstein, J. F. Banfield, J. A. Doudna (2020) A scoutRNA Is Required for Some Type V CRISPR-Cas Systems. Molecular Cell, Volume 79, Issue 3, 6 August 2020, Pages 416-424.e5,


421. A. Shafir, D. Azouri, EE. Goldberg, I. Mayrose (2020) Heterogeneity in the rate of molecular sequence evolution substantially impacts the accuracy of detecting shifts in diversification rates. Evolution, doi:


420. S. Bahiri-Elitzur and T. Tuller (2020) Computational discovery and modeling of novel gene expression rules encoded in the mRNA. Biochemical Society Transactions (2020),


419. I. Sason, D. Wojtowicz, W. Robinson, M. Leiserson, T. Przytycka and R. Sharan (2020) A Sticky Multinomial Mixture Model of Strand-Coordinated Mutational Processes in Cancer2. iScience, vol 23, 3, 1009002020.


418. Y.-A Kim, D. Wojtowicz, R. Sarto Basso, I. Sason, W. Robinson, D. Hochbaum, M. Leiserson, R. Sharan, F. Vandin, T. Przytycka (2020) Network-Based approaches elucidate di erences within APOBEC and clock-like signatures in breast cancer. Genome Medicine, 12:52,


417. I. Grigg, Y. Ivashko-Pachima*, T. A. Hait*, V. Korenková, O. Touloumi, R. Lagoudaki, A. Van Dijck, Z. Marusic, M. Anicic, J. Vukovic, R. F. Kooy, N. Grigoriadis & I. Gozes (2020) Tauopathy in the young autistic brain: novel biomarker and therapeutic target. Translational Psychiatry, volume 10, Article number: 228 (2020).  *contributed equally.


416. I. Sason,Y. Chen. M. D. M. Leiserson, R. Sharan (2020) A Mixture Model for Signature Discovery from Sparse Mutation Data. International Conference on Research in Computational Molecular Biology., RECOMB 2020: Research in Computational Molecular Biology pp 271-272. Part of the Lecture Notes in Computer Science book series (LNCS, volume 12074).


415.  N. Sagy,  S. Slovin,  M. Allalouf, M. Pour,  G. Savyon,  J. Boxman,  I. Nachman (2019) Prediction and control of symmetry breaking in embryoid bodies by environment and signal integration. Development 2019 146: dev181917.


414. M. LevyAmit Frishberg, I. Irit Gat-Viks (2020) Inferring Cellular Heterogeneity of Associations From Single Cell GenomicsBioinformatics, 2020 Mar 4;btaa151. doi: 10.1093/bioinformatics/btaa151. 


413. R. Wilentzik Müller and I. Gat-Viks (2020) Exploring Neural Networks and Related Visualization Techniques in Gene Expression Data. Front. Genet. 15 May 2020 |


412. Y. Steuerman, A. Wasserman, D. Zeltser, I. Shapira, D. Trotzky, P. Halpern, A. Meilik, E. Raykhshtat, S. Berliner, O. Rogowski, I. Gat-Viks & S. Shenhar-Tsarfaty (2019) Anemia measurements to distinguish between viral and bacterial infections in the emergency departmentEuropean Journal of Clinical Microbiology & Infectious Diseases, volume 38, pages 2331–2339.


411. D. Pellow, I. Mizrahi, R. Shamir (2020) PlasClass improves plasmid sequence classification. PLoS Computational Biology 16(4): e1007781 (2020).


410. Y. Zarai, Z. Zafrir, B. Siridechadilok, A. Suphatrakul, M. Ruppin, J. Julander, T. Tuller (2020) Evolutionary Selection against Short Nucleotide Sequences inViruses and their Related HostsDNA Res, dsaa008,


409. S. Bergman and T. Tuller (2020) Widespread non-modular overlapping codes in the coding regions. Physical Biology, Volume 17, Number 3.


408. D. Feder,  R. P. McGeary, N. Mitić, T. Lonhienne, A. Furtado, B. L. Schulz, R. J. Henry, S. Schmidt, L. W. Guddat, G. Schenk  (2020) Structural elements that modulate the substrate specificity of plant purple acid phosphatases: Avenues for improved phosphorus acquisition in crops. Plant Science 294 (2020) 110445.


407. M. Peeri & T. Tuller (2020) High-resolution modeling of the selection on local mRNA folding strength in coding sequences across the tree of life. Genome Biology, volume 21, Article number: 63 (2020).


406. H.S. Hayden, A. Eng, C. E. Pope, M. J. Brittnacher, A. T. Vo, E. J. Weiss, K. R. Hager, B. D. Martin, D. H. Leung, S. L. Heltshe, E. Borenstein, S. I. Miller & L. R. Hoffman (2020) Fecal dysbiosis in infants with cystic fibrosis is associated with early linear growth failure. Nature Medicine, 


405. T. Harel, N. Peshes-Yaloz, E. Bacharach, & I. Gat-Viks (2019) Predicting phenotypic diversity from molecular and genetic data. Genetics.


404. D. Coster, A. Wasserman, E. Fisher, O. Rogowski, D. Zeltser, I. Shapira, D. Bernstein, A. Meilik, E. Raykhshtat, P. Halpern, S. Berliner, S. Shenhar-Tsarfaty, R. Shamir (2019) Using the kinetics of C-reactive protein response to improve the differential diagnosis between acute bacterial and viral infections. Infection,


403. C. Noecker, H.C. Chiu, C. P. McNally, and E. Borenstein (2019) Defining and Evaluating Microbial Contributions to Metabolite Variation in Microbiome-Metabolome Association Studies. mSystems, 4:e00579-19, 2019.


402. I. Weiner, Y. Feldman, N. Shahar, I. Yacoby & T. Tuller (2019) CSO – A sequence optimization software for engineering chloroplast expression in Chlamydomonas reinhardtii. Algal Research, Vol 46, 


401. G. Dinstag, R. Shamir (2019) Prodigy: personalized prioritization of driver genes. Bionformatics, btz815,


400. S. Mandelboum Z. Manber, O. Elroy-Stein, R. Elkon (2019) Recurrent functional misinterpretation of RNA-seq data caused by sample-specific gene length bias. PLoS Biol. 2019 Nov 12;17(11):e3000481.


399. B.D. Ross, A.J. Verster, M.C. Radey, D.T. Schmidtke, C.E. Pope, L.R. Hoffman, A.M. Hajjar, S.Brook Peterson, E. Borenstein & J.D. Mougous (2019) Human gut bacteria contain acquired interbacterial defence systems. Nature (2019) doi:10.1038/s41586-019-1708-z.


398. G. Ling, D. Miller, R. Nielsen, A. Stern (2019) A Bayesian framework for inferring the influence of sequence context on point mutations. Molecular Biology and Evolution, msz248,


397. V. Dubinsky,  L. Reshef,  N. Bar,  D. Keizer,  N. Golan,  K. Rabinowitz,  L. Godny,  K. Yadgar,  K. Zonensain,  H. Tulchinsky,  U. Gophna AND I. Dotan  (2019) Predominantly Antibiotic-resistant Intestinal Microbiome Persists in Patients With Pouchitis Who Respond to Antibiotic Therapy. Gastroenterology 158 (2020) pp. 597-611.  doi:


396.  I. Weiner, N. Shahar, P. Marco, I. Yacoby, T. Tuller (2019) Solving the riddle of the evolution of Shine-Dalgarno based translation in chloroplasts. Molecular Biology and Evolution, msz210,


395. E. D. Shulman, R. Elkon (2019) Cell-type-specific analysis of alternative polyadenylation using single-cell transcriptomics data. Nucleic Acids Research,  gkz781,


394. E. Persi, D. Prandid, Y. I. Wolf, Y. Pozniake, G. D. Barnabase, K. Levanonf, I. Barshackh, C. Barbierii, P. Gasperinid, H. Beltranj, B. M. Faltasj, M. A. Rubin, T. Geiger, E. V. Koonin, F. Demichelisd, and D. Horn (2019) Proteomic and genomic signatures of repeat instability in cancer and adjacent normal tissues. PNAS,


393. I. Sason, D. Wojtowicz, W. Robinson, M. D. M. Leiserson, T. M. Przytycka, R. Sharan (2019) A Sticky Multinomial Mixture Model of Strand-Coordinated Mutational Processes in Cancer. International Conference on Research in Computational Molecular Biology

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392. N. Rappoport and R. Shamir (2019) Inaccuracy of the log‐rank approximation in cancer data analysis. Molecular Systems Biology (2019)15:e8754


391. G. Dinstag, D. Amar, E. Ingelsson, E. Ashley and R. Shamir (2019) Personalized prediction of adverse heart and kidney events using baseline and longitudinal data from SPRINT and ACCORD. PLOS ONE,


390. T. Zinger,  M. Gelbart,  D. Miller,  P. S. Pennings and A.Stern (2019) Inferring population genetics parameters of evolving viruses using time-series data. Virus Evolution, Vol 5, Issue 1, January 2019, vez011,


389. T. A. Hait, A.Maron-Katz., D. Sagir, D. Amar, I. Ulitsky, C. Linhart, A. Tanay, R. Sharan, Y. Shiloh, R. Elkon, R.Shamir (2019) The EXPANDER integrated platform for transcriptome analysis. Journal of Molecular Biology, (2019).


388. O. Avram, D. Rapoport, S. Portugez and T. Pupko (2019) M1CR0B1AL1Z3R—a user-friendly web server for the analysis of large-scale microbial genomics data. Nucleic Acids Research, gkz423,


387. R. Sabi & T. Tuller (2019) Novel insights into gene expression regulation during meiosis revealed by translation elongation dynamics. Nature-Npj, Systems Biology and Applications, volume 5, Article number: 12 (2019).


386. A. Frishberg, N. Peshes-Yaloz, O. Cohn, D. Rosentul, Y. Steuerman, L. Valadarsky, G. Yankovitz, M. Mandelboim, F. A. Iraqi, I. Amit, L. Mayo, E. Bacharach and I. Gat-Viks (2019) Cell composition analysis of bulk genomics using single-cell data. Nature Methods,


385. N. Shahar, I. Weiner, L. Stotsky, T. Tuller and I. Yacoby (2019) Prediction and large-scale analysis of primary operons in plastids reveals unique genetic features in the evolution of chloroplasts. Nucleic Acids Research, gkz151,


384.  S. Abadi, D. Azouri, T. Pupko and I. Mayrose (2019) "Model selection may not be a mandatory step for phylogeny reconstruction".  Nature Communications 10, no. 1 (2019): 934.


383. T. Kustin, G. Ling, S. Sharabi, D. Ram, N. Friedman, N. Zuckerman, ED Bucris, A. Glatman-Freedman,  A. Stern, M. Mandelboim  (2019)  A method to identify respiratory virus infections in clinical samples using next-generation sequencing. Scientific Reports. 2019 Feb 22;9(1):2606.


382. Y. Tatour, J. Tamaiev, S. Shamaly, R. Colombo, E Bril, T. Rabinowitz, A. Yaakobi, E. Mezer, R. Leibu, B. Tiosano, N. Shomron, I. Chowers, E. Banin, D. Sharon, T. Ben-Yosef (2019) A novel intronic mutation of PDE6B is a major cause of autosomal recessive retinitis pigmentosa among Caucasus Jews. Molecular Vision 2019; 25:155-164,


381. T. Rabinowitz, A. Polsky, D. Golan, A. Danilevsky, G. Shapira, C. Raff, L. Basel-Salmon, R. Tomashov Matar,and N. Shomron (2019) Bayesian-based noninvasive prenatal diagnosis of single-gene disorders. Genome Research, doi: 10.1101/gr.235796.118.


380. E. Shteyer, L. Shekhtman, T. Zinger,  S.Harari, I. Gafanovich, D. Wolf , et al. (2019) Modeling suggests that microliter volumes of contaminated blood caused an outbreak of hepatitis C during computerized tomography. PLoS ONE 14(2): e0212252.


379.  T. Tuller, A. Diament, A. Yahalom, A. Zemach, S. Atar and D. A. Chamovitz (2019) The COP9 signalosome influences the epigenetic landscape of Arabidopsis thaliana. Bioinformatics, 1–6, doi: 10.1093/bioinformatics/bty1053.


378.  B. Slobodin, R. Han, V. Calderone, JA.Vrielink, F. Loayza-Puch, R. Elkon, R. Agami (2017) Transcription Impacts the Efficiency of mRNA Translation via Co-transcriptional N6-adenosine Methylation. Cell, 169(2):326-337. (*co-corresponding authors).


377.  L. Li, PC. van Breugel, F. Loayza-Puch, AP. Ugalde, G. Korkmaz, N. Messika-Gold, R. Han, R. Lopes, EP. Barbera, H. Teunissen, de E. Wit, RJ. Soares, BS. Nielsen, mK. Holmstrø, DJ. Martìnez-Herrera , M. Huarte, A. Louloupi, J. Drost, R. Elkon , R. Agami (2018)  LncRNA-OIS1 regulates DPP4 activation to modulate senescence induced by RAS. Nucleic Acids Res. 4;46(8):4213-4227. (*co-corresponding authors).


376.  Han R, Li L, Ugalde AP, Tal A, Manber Z, Barbera EP, Chiara VD, Elkon R, Agami R. Functional CRISPR screen identifies AP1-associated enhancer regulating FOXF1 to modulate oncogene-induced senescence. Genome Biol. 2018 Aug 17;19(1):118. 


375. Lopes R, Korkmaz G, Revilla SA, van Vliet R, Nagel R, Custers L, Kim Y, van Breugel PC, Zwart W, Moumbeini B, Manber Z, Elkon R, Agami R. CUEDC1 is a primary target of ERa essential for the growth of breast cancer cells. Cancer Lett. 2018 Nov 1;436:87-95.


374.  Chessum L, Matern MS, Kelly MC, Johnson SL, Ogawa Y, Milon B, McMurray M, Driver EC, Parker A, Song Y, Codner G, Esapa CT, Prescott J, Trent G, Wells S, Dragich AK, Frolenkov GI, Kelley MW, Marcotti W, Brown SDM, Elkon R, Bowl MR, Hertzano R. Helios is a key transcriptional regulator of outer hair cell maturation. Nature. 2018 Nov;563(7733):696-700.


373.  N. Rappoport and R. Shamir (2019) NEMO: Cancer subtyping by integration of partial multi-omic data. Bioinformatics, btz058,


372.  N. Rappoport and R. Shamir (2018). Multi-omic and multi-view clustering algorithms: review and cancer benchmark. Nucleic Acids Research, 46(20), 10546–10562.


371.  M. Drori, A. Rice,  M. Einhorn,  O. Chay, L. Glick & I. Mayrose (2018) OneTwoTree: An online tool for phylogeny reconstructionMolecular ecology resources18(6), 1492-1499.   


370. A. Rice, P. Šmarda, M. Novosolov, M. Drori, L. Glick, N. Sabath, S. Meiri, J. Belmaker and I. Mayrose (2019) The global biogeography of polyploid plants. Nature Ecology & Evolution, 3(2), p.265.  


369. A. Diament I. Weiner,  N. Shahar,  S. Landman,  Y. Feldman,  S. Atar, M. Avitan,  S. Schweitzer,  I. Yacoby and  T. Tuller (2019) ChimeraUGEM: unsupervised gene expression modeling in any given organism. Bioinformatics, btz080,


368. E. Dafni, I. Weiner, N. Shahar, T. Tuller and I. Yacoby (2019) Image-processing software for high-throughput quantification of colony luminescence​.  mSphere 4:e00676-18. https://


367. K. Levinstein Hallak, S. Tzur and S. Rosset (2018) Big data analysis of human mitochondrial DNA substitution models: a regression approach. BMC Genomics, 19:759,


366. G. Masrati , M. Dwivedi, A. Rimon, Y. Gluck-Margolin, A. Kessel , H. Ashkenazy, I. Mayrose, E. Padan and N. Ben-Tal (2018) Broad phylogenetic analysis of cation/proton antiporters reveals transport determinants. Nature Communications, volume 9, Article number: 4205. 


365. E. Rahmani,  R. Schweiger,  L. Shenhav,  T. Wingert,  I. Hofer, E. Gabel,  E. Eskin and  E. Halperin (2018) BayesCCE: a Bayesian framework for estimating cell-type composition from DNA methylation without the need for methylation referenceGenome Biology, 201819:141.


364. I. Nurick, R. Shamir and R. Elkon (2018) Genomic meta-analysis of the interplay between 3D chromatin organization and gene expression programs under basal and stress conditions. Epigenetics & Chromatin (2018) 11:49


363. O. Avram, A. Vaisman-Mentesh, D. Yehezkel, H. Ashkenazy, T. Pupko and Y. Wine (2018) ASAP - A Webserver for Immunoglobulin-Sequencing Analysis Pipeline. Front. in Immunol.,


362. A. Diament and T. Tuller (2018) Modeling three-dimensional genomic organization in evolution andpathogenesis. Seminars in Cell & Developmental Biology,


361. J. Mohamad, O. Sarig, L. M. Godsel, A. Peled, N. Malchin, R. Bochner, D. Vodo, T. Rabinowitz, M. Pavlovsky, S. Taiber, M. Fried, M Eskin-Schwartz, S. Assi, N. Shomron, J. Uitto, J. L. Koetsier, R. Bergman, K. J. Green and E. Sprecher,(2018) Filaggrin 2 Deficiency Results in Abnormal Cell-Cell Adhesion in the Cornified Cell Layers and Causes Peeling Skin Syndrome Type A. Journal of Investigative Dermatology (2018). doi:10.1016/j.jid.2018.04.032.


360. K. Theys, A. Feder, M. Gelbart, M. Hart, A. Stern (2018) Pennings PS. Within-patient mutation frequencies reveal fitness costs of CpG dinucleotides and drastic amino acid changes in HIVPLoS Genetics, Jun 28;14(6):e1007420 (2018).


359. K. Perl, R. Shamir and K. B. Avraham (2018) Computational analysis of mRNA expression profiling in the inner ear reveals candidate transcription factors associated with proliferation, differentiation, and deafness. Human Genomics,, 2018.


358. I. Weiner, N. Shahar, Y. Feldman, S. Landman, Y. Milrad, O. Ben-Zvi, M. Avitan, E. Dafni, S. Schweitzer, H. Eilenberg, S. Atar, A. Diament, T. Tuller and I. Yacoby (2018) Overcoming the expression barrier of the ferredoxin‑hydrogenase chimera in Chlamydomonas reinhardtii supports a linear increment in photosynthetic hydrogen output. Algal Research, Vol. 33, July 2018, Pp. 310–315.


357.G. Hyams, S. Abadi, S. Lahav, A. Avni, E. Halperin, E. Shani, I. Mayrose (2018) CRISPys: Optimal sgRNA design for editing multiple members of a gene family using the CRISPR systemJournal of molecular biology, 20;430(15):2184-2195.


356. E. Goz, Y. Tsalenchuck, R. O. Benaroya, Z. Zafrir, S. Atar, T. Altman, J. Julander and T. Tuller (2018) Generation and comparative genomics of synthetic dengue viruses. BMC Bioinformatics 2018, 19(Suppl 6):140, 


355. E. Goz, Z. Zafrir and T. Tuller (2018) Universal evolutionary selection for high dimensional silent patterns of information hidden in the redundancy of viral genetic code. Bioinformatics, bty351, doi: 10.1093/bioinformatics/bty351. 


354. R. Zeira and R. Shamir (2018) Sorting cancer karyotypes using double-cut-and-joins, duplications and deletions. Bioinformatics, bty381,  


353. T. A. Hait, D. Amar, R. Shamir and R. Elkon (2018) FOCS: a novel method for analyzing enhancer and gene activity patterns infers an extensive enhancer-promoter map. Genome Biology, 19:56,, 2018. 


352. Zarai Y, Tuller T. (2018) Computational analysis of the oscillatory behavior at the translation level induced by mRNA levels oscillations due to finite intracellular resources. PLoS Comput Biol. 3;14(4):e1006055. doi: 10.1371/journal.pcbi.1006055. 


351. I. Weiner, S. Atar, S. Schweitzer, H. Eilenberg, Y. Feldman, M. Avitan, M. Blau, A. Danon, T. Tuller and I. Yacoby (2018) Enhancing heterologous expression in Chlamydomonas reinhardtii by transcript sequence optimization. The Plant Journal, doi: 10.1111/tpj.13836. 


350. D. Vodo, O. Sarig, D. Jeddah, N. Malchin, M. Eskin-Schwarz, J. Mohamad, T. Rabinowitz, I. Goldberg, N. Shomron, Z. Khamaysi, R. Bergman, E. Sprecher (2018) Punctate palmoplantar keratoderma: an unusual mutation causing an unusual phenotype. Br J Dermatol. 2018 Mar 1. doi: 10.1111/bjd.16502. 

349. A. Diament, A. Feldman, E. Schochet, M. Kupiec, Y. Arava, T. Tuller (2018) The extent of ribosome queuing in budding yeast. PLoS Comput Biol 14(1): e1005951. 


348. D. Amar, A. Vizel, C. Levy and R. Shamir (2018) ADEPTUS: A discovery tool for disease prediction, enrichment and network analysis based on profiles from many diseases. Bioinformatics, bty027, 


347. H. Sameach, A. Narunsky ..., T. Juven-Gershon, N. Ben-Tal, S. Ruthstein (2017) Structural and Dynamics Characterization of the MerR Family Metalloregulator CueR in its Repression and Activation States. Structure, Volume 25, Issue 7, 5 July 2017, Pages 988-996.


346. A. Mushegiana, E. Levy Karin and T. Pupko (2018) Sequence analysis of malacoherpesvirus proteins: Pan-herpesvirus capsid module and replication enzymes with an ancient connection to "Megavirales". Virology, Vol. 513, pp. 114-128. 


345. E. Cohen, Z. Zafrir & T. Tuller (2017) A code for transcription elongation speed. RNA Biology, DOI: 10.1080/15476286.2017.1384118. 


344. G. Hyams, D. Greenfeld and D. Bank (2017) Improved Training for Self Training by Confidence Assessments. CoRR, arXiv:1710.00209abs/1710.00209 (2017). 


343. O. Mioduser, E. Goz and T. Tuller (2017) Significant differences in terms of codon usage bias between bacteriophage early and late genes: a comparative genomics analysis. BMC Genomics, 18:866, DOI 10.1186/s12864-017-4248-7. 


342. Y. Orenstein, D. Pellow, G. Marcais, R. Shamir, C. Kingsford (2017) Designing small universal k-mer hitting sets for improved analysis of high-throughput sequencingPLoS Computational Biology, 


341. S. Abadi, W. X. Yan, D. Amar, I. Mayrose (2017) A machine learning approach for predicting CRISPR-Cas9 cleavage efficiencies and patterns underlying its mechanism of action. PLoS Comput Biol 13(10): e1005807.


340. E. Goz, Y. Tsalenchuck, R. Oren Benaroya, S. Atar, T. Altman , J. Ju-lander, T. Tuller (2017) Generation and Comparative Genomics of Synthetic Dengue Viruses. In: Meidanis J., Nakhleh L. (eds) Comparative Genomics. RECOMB-CG 2017. Lecture Notes in Computer Science, vol 10562. Springer. 


339. R. Zeira, M. Zehavi and R. Shamir (2017) A Linear-Time Algorithm for the Copy Number Transformation Problem. J. of Computational Biology, DOI: 10.1089/cmb.2017.0060, 2017. 


338. Y. Zarai, M. Margaliot and T. Tuller (2017) Ribosome Flow Model with Extended Objects. J. Royal Society Interface, vol. 14, no. 135, p. 20170128, 2017. 


337. T. A. Hait, D. Amar, R. Shamir and R. Elkon (2017) An extensive enhancer-promoter map generated by genome-scale analysis of enhancer and gene activity patternsGenome Biology, doi: 10.1186/s13059-018-1432-2


336. Y. Zarai, A. Ovseevich and M. Margaliot (2017) Optimal Translation Along a Circular mRNA. Scientific Reports, vol. 7, no. 9464.


335. Y. Zarai, M. Margaliot and A. B. Kolomeisky (2017) A Deterministic Model for One-Dimensional Excluded Flow with Local Interactions. PLoS ONE, 12(8): e0182074. 


334. Y. Zarai, M. Margaliot, T. Tuller (2017) A deterministic mathematical model for bidirectional excluded flow with Langmuir kinetics. PLoS ONE, 12(8): e0182178. 


333. M. ElKebir, B. J. Raphael, R. Shamir, R. Sharan, S. Zaccaria, M. Zehavi and R. Zeira (2017) Complexity and algorithms for copy-number evolution problems. Algorithms Mol Biol, 12:13. DOI: 10.1186/s13015-017-0103-2. 


332. G. Marçais, D. Pellow, D. Bork, Y. Orenstein, R. Shamir and C. Kingsford (2017) Improving the performance of minimizers and winnowing schemes. Bioinformatics, special issue of ISMB/ECCB 2017, Vol. 33, i110-i117, doi: 10.1093/bioinformatics/btx235 (2017). 


331. Y. Zarai, M. Margaliot, E. D. Sontag and T. Tuller (2017) Controllability analysis and control synthesis for the ribosome flow model. Controlling mRNA Translation. IEEE/ACM Trans Comput Biol Bioinform, doi: 10.1109/TCBB.2017.2707420. 


330. K. Perl, K. Ushakov, Y. Pozniak, O. Yizhar-Barnea, Y. Bhonker, S. Shivatzki, T. Geiger, K.B. Avraham and R. Shamir (2017) Reduced changes in protein compared to mRNA levels across non-proliferating tissues. BMC Genomics, 18:305, DOI 10.1186/s12864-017-3683-9, 2017.


329. R. Sabi and T. Tuller (2017) Computational Analysis of Nascent Peptides that Induce Ribosome Stalling and Their Proteomic Distribution in Saccharomyces cerevisiae. RNA, doi:10.1261/rna.059188.116. 


328. R. Rozov, G. Goldshlager, E. Halperin, R. Shamir (2017) Faucet: streaming de novo assembly graph construction. Bioinformatics, DOI: 


327. A. Diament and T. Tuller (2017) Tracking the evolution of 3D gene organization demonstrates its connection to phenotypic divergence. Nucleic Acids Research, 1, DOI: 10.1093/nar/gkx205. 


326. A. Stern, M. Te Yeh, T. Zinger, M. Smith, C. Wright, G. Ling, R. Nielsen, A. Macadam and R. Andino (2017) The Evolutionary Pathway to Virulence of an RNA Virus. Cell,  


325. E. Rahmani, L. Shenhav, R.Schweiger, P. Yousefi, K. Huen, B. Eskenazi, C. Eng, S. Huntsman, D. Hu, J. Galanter, S. Oh, M. Waldenberger, K. Strauch, H. Grallert, T. Meitinger, C. Gieger, N. Holland, E. Burchard, N. Zaitlen and E. Halperin (2017) Genome-wide methylation data mirror ancestry information. . Epigenetics & Chromatin, DOI: 10.1186/s13072-016-0108-y. 


324. E. Rahmani, R. Yedidim, L. Shenhav, R. Schweiger, O. Weissbrod, N. Zaitlen and E. Halperin (2017) GLINT: a user-friendly toolset for the analysis of high-throughput DNA-methylation array data. Bioinformatics, DOI: 


323. E. Rahmani, N. Zaitlen, Y. Baran, C. Eng, D. Hu, J. Galanter, S. Oh, E. G. Burchard, E. Eskin, J. Zou & E. Halperin (2017) Correcting for cell-type heterogeneity in DNA methylation: a comprehensive evaluation. Nature Methods, 14, 218-219, doi:10.1038/nmeth.4190. 


322. E. Goz, O. Mioduser, A. Diament and T. Tuller (2017) Evidence of translation efficiency adaptation of the coding regions of the bacteriophage lambda. DNA Research, 1-10, doi: 10.1093/dnares/dsx005. 


321. D. Silverbush, S. Grosskurth, D. Wang, F. Powell, B. Gottgens, J. Dry and J. Fisher (2017) Cell-Specific Computational Modeling of the PIM Pathway in Acute Myeloid Leukemia. Cancer Research, doi: 10.1158/0008-5472.CAN-16-1578. 


320. L. Yang, Y. Orenstein, A. Jolma, Y. Yin, J. Taipale, R. Shamir and R. Rohs (2017) Transcription factor family-specific DNA shape readout revealed by quantitative specificity models. Molecular Systems Biology, 13, 910, DOI 10.15252/msb.20167238, 2017. 


319. Z. Zafrir and T. Tuller (2017) Unsupervised detection of regulatory gene expression information in different genomic regions enables gene expression ranking. BMC Bioinformatics, 18:77, DOI: 10.1186/s12859-017-1497-z. 


318. G. Marcais, D. Pellow, D. Bork, Y. Orenstein, R. Shamir, C. Kingsford (2017) Improving the performance of minimizers and winnowing schemes. BioarXiv, DOI: 


317. D. Amar, S. Izraeli and R. Shamir. (2017) Utilizing somatic mutation data from numerous studies for cancer research: proof of concept and applications. Oncogene, DOI:10.1038/onc.2016.489. 


316. R. Rozov, A. Brown Kav, D. Bogumil, N. Shterzer, E. Halperin, I. Mizrahi, and R. Shamir (2016) Recycler: an algorithm for detecting plasmids from de novo assembly graphs. Bioinformatics, 10.1093/bioinformatics/btw651.


315. P. Singmann D. Shem Tov........Y. Baran, S. Guarrera, P. Vineis....M. Waldenberger and E. Halperin (2015) Characterization of whole-genome autosomal differences of DNA methylation between men and women. Epigenetics & Chromatin 8:43, DOI 10.1186/s13072-015-0035-3. 


314. A. Diament and T. Tuller (2016) Three-dimensional Genomic Organization of Genes' Function in Eukaryotes. Chapter 14 in a book: Evolutionary Biology, Editor: P. Pontarotti, pp: 233-252, DOI: 10.1007/978-3-319-41324-2_14. 


313. R. Schweiger, S. Kaufman, R. Laaksonen, M. E. Kleber, W. März, E. Eskin, S. Rosset, and E. Halperin (2016) Fast and accurate construction of confidence intervals for heritability. The American Journal of Human Genetics, 98, no. 6 (2016): 1181-1192. 


312. R. Sabi, R. Volvovitch Daniel and T. Tuller (2016) stAIcalc: tRNA Adaptation Index Calculator based on Species-Specific weights. Bioinformatics, Bioinformatics, doi: 10.1093/bioinformatics/btw647. 


311. A. Gilam, J. Conde, D. Weissglas-Volkov, N. Oliva, E. Friedman, N. Artzi, N. Shomron (2016) Local microRNA delivery targets Palladin and prevents metastatic breast cancer. Nature Communications, 7:12868, DOI: 10.1038/ncomms12868. 


310. Y.Y. Waldman, A. Biddanda, M. Dubrovsky, C. L. Campbell, C. Oddoux, E. Friedman, G. Atzmon, E. Halperin, H. Ostrer, A. Keinan (2016) The genetic history of Cochin Jews from India. Human Genetics 135:1127-1143. doi:10.1007/s00439-016-1698-y. 


309. D. Chen, Y. Orenstein, R. Golodnitsky, M. Pellach, D. Avrahami, C. Wachtel, A. Ovadia-Shochat, H. Shir-Shapira, A. Kedmi, T. Juven-Gershon, R. Shamir, D. Gerber (2016) SELMAP - SELEX affinity landscape MAPping of transcription factor binding sites using integrated microfluidics. Scientific Reports, 6, 33351; doi: 10.1038/srep33351, 2016. 


308. I. Ben-Bassat and B. Chor (2016) CRISPR Detection From Short Reads Using Partial Overlap Graphs. Journal of Computational Biology, Volume 23, Pp. 461-471, DOI: 10.1089/cmb.2015.0226. 


307. A. Frishberg, A. Brodt, Y. Steuerman and I. Gat-Viks (2016) ImmQuant: a user-friendly tool for inferring immune cell type composition from gene expression data. Bioinformatics 2016; doi: 10.1093/bioinformatics/btw535. 


306. Y. Orenstein, D. Pellow, G. Marcais, R. Shamir, C. Kingsford (2016) Compact universal k-mer hitting sets. Proceedings of WABI 2016, Aarhus, Denmark, August, 2016, LNCS 9838 pp. 257--268 (2016). 


305. M. El-Kebir, B. Raphael, R. Shamir, R. Sharan, S. Zaccaria, M. Zehavi, R. Zeira (2016) Copy-Number Evolution Problems: Complexity and Algorithms. Proceedings of WABI 2016, Aarhus, Denmark, August, 2016,LNCS 9838 pp. 137-149 (2016). 


304. Y. Orenstein and R. Shamir (2016) Modeling protein-DNA binding via high throughput in vitro technologies. Briefings in Functional Genomics, doi: 10.1093/bfgp/elw030. 


303. A. Salman-Minkov, N. Sabath and I. Mayrose (2016) Whole-genome duplication as a key factor in crop domestication. Nature Plants, 2, Article number: 16115, doi:10.1038/nplants.2016.115. 


302. A. Maron-Katz, D. Amar, E. Ben-Simon, T. Hendler, R. Shamir (2016) RichMind: a tool for improved inference from large-scale neuroimaging results. PLoS One, DOI:10.1371/journal.pone.0159643 (2016). 


301. H. J. A-T Atamni, M. Botzman, R. Mott, I. Gat-Viks, F. A. Iraqi (2016) Mapping liver fat female-dependent quantitative trait loci in collaborative cross mice. Mamm Genome, DOI 10.1007/s00335-016-9658-3. 


300. E. Goz and T. Tuler (2016) Evidence of a Direct Evolutionary Selection for Strong Folding and Mutational Robustness Within HIV Coding Regions. Journal of Computational Biology, Vol 23, Number 8, Pp. 1-10, DOI: 10.1089/cmb.2016.0052. 


299. R. Shamir, Meirav Zehavi and R. Zeira (2016) A Linear-Time Algorithm for the Copy Number Transformation Problem. 27th Annual Symposium on Combinatorial Pattern Matching (CPM 2016). Editors: Roberto Grossi and Moshe Lewenstein; LIPICS, Article No. 16; pp. 16:1-16:13.


298. Z. Zafrir, H. Zur and T. Tuller (2016) Selection for reduced translation costs at the intronic 5' end in fungi. DNA Research, doi: 10.1093/dnares/dsw019. 


297. A. Diament and T. Tuller (2016) Estimation of ribosome profiling performance and reproducibility at various levels of resolution. Biology Direct, 11:24, DOI 10.1186/s13062-016-0127-4. 


296. Y. Steuerman and I. Gat-Viks (2016) Exploiting Gene-Expression Deconvolution to Probe the Genetics of the Immune System. PLoS Comput Biol 12(4): e1004856. 


295. M. Botzman, A. Nachshon, A. Brodt and I. Gat-Viks (2016) POEM: Identifying joint additive effects on regulatory circuits. Front. Genet. 7:48, doi: 10.3389/fgene.2016.00048. 


294. E. Rahmani, N. Zaitlen, Y. Baran, C. Eng, D. Hu, J. Galanter, S. Oh, E.G. Burchard, E. Eskin, J. Zou & E. Halperin (2016) Sparse PCA corrects for cell type heterogeneity in epigenome-wide association studies. Nature Methods, doi:10.1038/nmeth.3809. 


293. Y.Y. Waldman, A. Biddanda, N. R. Davidson, P. Billing-Ross, M. Dubrovsky, C. L. Campbell, C. Oddoux, E. Friedman, G. Atzmon, E. Halperin, H. Ostrer, A. Keinan (2016) The Genetics of Bene Israel from India Reveals Both Substantial Jewish and Indian Ancestry. PLoS ONE 11(3): e0152056. doi:10.1371/ journal.pone.0152056.


292. D. Hollander, M. Donyo, N. Atias, K. Mekahel, Z. Melamed, S. Yannai, G. Lev-Maor, A. Shilo, S. Schwartz, I. Barshack, R. Sharan and G. Ast (2016) A network-based analysis of colon cancer splicing changes reveals a tumorigenesis-favoring regulatory pathway emanating from ELK1. Genome Research, 26:1-13, doi:10.1101/gr.193169.115. 


291. E. Levy Karin, A. Rabin, H. Ashkenazy, D. Shkedy, O. Avram, R. A. Cartwright and T. Pupko (2015) Inferring indel parameters using a simulation-based approach. Genome Biology and Evolution. 2015; 7:3226-3238. 


290. A. Domingo, D. Amar, K. Grütz, L. Lee, R. Rosales, N. Brüggemann, R. D. Jamora, E. Cutiongco dela-Paz, K. Lohmann, R. Shamir, C. Klein, A. Westenberger (2016) Evidence of TAF1 dysfunction in peripheral models of X-linked dystonia-parkinsonism. Cellular and Molecular Life Sciences. DOI 10.1007/s00018-016-2159-4.

289. A. Narunsky, S. Nepomnyachiy, H. Ashkenazy, R. Kolodny, N. Ben-Tal (2015) ConTemplate suggests possible alternative conformations for a query protein of known. Structure 23, 2162-2170. 


288. Y. Glick, Y. Orenstein, D. Chen D, D. Avrahami, T. Zor, R. Shamir, D. Gerber (2015) Integrated microfluidic approach for quantitative high-throughput measurements of transcription factor binding affinities. Nucleic Acids Research, doi: 10.1093/nar/gkv1327. 


287. I. Sela, H. Ashkenazy, K. Kazutaka, and T. Pupko (2015) GUIDANCE2: accurate detection of unreliable alignment regions accounting for the uncertainty of multiple parameters. Nucleic Acids Research, 43(W1):W7-W14. 


286. R. Rozov, A. Kav Brown, D. Bogumil, E. Halperin, I. Mizrahi, R. Shamir (2015) Recycler: an algorithm for detecting plasmids from de novo assembly graphs. bioRxiv, DOI: 


285. R. Elkon, B. Milon, L. Morrison, M. Shah, S. Vijayakumar, M. Racherla, C. C. Leitch, L. Silipino, S. Hadi, M. Weiss-Gayet, E. Barras, C. D. Schmid, A. Ait-Lounis, A. Barnes, Y Song, D. J. Eisenman, E. Eliyahu, G. I. Frolenkov, S. E. Strome, B. Durand, N. A. Zaghloul, S. M. Jones, W. Reith & R. Hertzano (2015) RFX transcription factors are essential for hearing in mice. Nature Communications,6:8549,DOI: 10.1038. 


284. Y. Margalit, Y. Baran and E. Halperin(2015) Multiple-Ancestor Localization for Recently Admixed Individuals. Proceedings of the 15th Annual Workshop on Algorithms in Bioinformatics (WABI) 2015.


283. E. Goz and T. Tuller (2015) Widespread signatures of local mRNA folding structure selection in four Dengue virus serotypes. BMC Genomics, 16(Suppl 10):S4. 


282. R. Sabi and T. Tuller (2015) A comparative genomics study on the effect of individual amino acids on ribosome stalling. BMC Genomics, 16(Suppl 10):S5. 


281. T. Ben-Yehezkel, S.Atar, H. Zur, A. Diament, E. Goz, T. Marx, R. Cohen, A. Dana, A. Feldman, E. Shapiro and T. Tuller (2015) Rationally designed, heterologous S. cerevisiae transcripts expose novel expression determinants. RNA Biology 12:9, 972--984. 


280. N. Pillar , L. Yoffe ,M. Hod and N. Shomron (2014) The possible involvement of microRNAs in preeclampsia and gestational diabetes mellitus.  Best Pract Res Clin Obstet Gynaecol 29(2):176-82. doi: 10.1016/j.bpobgyn.2014.04.021. 


279. O. Isakov, D. Lev, L. Blumkin, G. Celniker, E. Leshinsky-Silver and N. Shomron (2015) Crowdfunding effort identifies the causative mutation in a patient with nystagmus, microcephaly, dystonia and hypomyelination. J Genet Genomics, vol. 42, no. 2, pp. 79-81. 


278. O. Isakov, A. V. Bordería, D. Golan, A. Hamenahem, G. Celniker, L. Yoffe, H. Blanc, M. Vignuzzi and N. Shomron (2015) Deep sequencing analysis of viral infection and evolution allows rapid and detailed characterization of viral mutant spectrum. Bioinformatics, 1-10, doi: 10.1093/bioinformatics/btv101. 


277. A. Rudnicki, O. Isakov, K. Ushakov, S. Shivatzki, I. Weiss, L. M. Friedman, N. Shomron and K. B. Avraham (2014) Next-generation sequencing of small RNAs from inner ear sensory epithelium identifies microRNAs and defines regulatory pathways. BMC Genomics, vol. 15, p. 484, 2014. 


276. D. Amar, T. Hait, S. Izraeli and R. Shamir (2015) Integrated analysis of numerous heterogeneous gene expression profiles for detecting robust disease-specific biomarkers and proposing drug targets. Nucleic Acids Research 2015; doi: 10.1093/nar/gkv810. 


275. NM. Kopelman,J. Mayzel, M. Jakobsson , NA. Rosenberg , I. Mayrose (2015) Clumpak: a program for identifying clustering modes and packaging population structure inferences across K. Mol Ecol Resour. doi: 10.1111/1755-0998.12387.


274. Z. Zafrir and T. Tuller (2015) Nucleotide sequence composition adjacent to intronic splice sites improves splicing efficiency via its effect on pre-mRNA local folding in fungi. RNA, 21:1-15. 


273. R. Edri, Y. Yaffe, M. J. Ziller, N. Mutukula, R. Volkman, E. David, J. Jacob-Hirsch, H. Malcov, C. Levy, G. Rechavi, I. Gat-Viks, A. Meissner& Y. Elkabetz (2015) Analysing human neural stem cell ontogeny by consecutive isolation of Notch active neural progenitors. Nat Commun. 2015 Mar 23;6:6500. doi: 10.1038/ncomms7500. 


272. I. Gat-Viks, T. Geiger, M. Barbi, G. Raini, O. Elroy-Stein (2015) Proteomics-level analysis of myelin formation and regeneration in a mouse model for Vanishing White Matter disease. J Neurochem ;134(3):513-26. doi: 10.1111/jnc.13142. Epub 2015 May 14. 


271. Y. Oren, A. Nachshon, A. Frishberg, R. Wilentzik and I. Gat-Viks (2015) Linking traits based on their shared molecular mechanisms. eLife, 2015;4:e04346. DOI: 10.7554/eLife.04346.


270. R. Wilentzik and I. Gat-Viks (2015) A statistical framework for revealing signaling pathways perturbed by DNA variants. Nucleic Acids Research, 2015, Vol. 43, No. 11 e74, doi: 10.1093/nar/gkv203. 


269. A. Sloutskin, Y. M. Danino, Y. Zehavi, Y. Orenstein, T. Doniger, R. Shamir, T. Juven-Gershon (2015) ElemeNT: A computational tool for detecting core promoter elements. Transcription, 6:3, 41--50. 


268. J. Y. Zou, E.Halperin, E.Burchard and S.Sankararaman (2015) Inferring parental genomic ancestries using pooled semi-Markov processes. Bioinformatics, 31 (12) : i190-i196, 2015. 


267. Y. Baran and E. Halperin (2015) A Note on the Relations Between Spatio-Genetic Models. Journal of Computational Biology, DOI: 10.1089/cmb.2015.0080. 


266. Y. Baran et al. (2015) The landscape of genomic imprinting across diverse adult human tissues. Genome research: gr-192278. 


265. N. Amir, D. Cohen and H. Wolfson (2015) "DockStar: a Novel ILP based Integrative Method for Structural Modelling of Multimolecular Protein Complexes (Extended Abstract). Lecture Notes in Computer Science, Research in Computational Molecular Biology, Volume 9029, 2015, pp 13-15. 


264. N. Amir, D. Cohen and H. Wolfson (2015) "DockStar: a Novel ILP based Integrative Method for Structural Modeling of Multimolecular Protein Complexes. Bioinformatics, doi: 10.1093/bioinformatics/btv270. 


263. R. Zeira and R. Shamir (2015) "Sorting by cuts, joins and whole chromosome duplications". Proceedings of CPM 2015, Ischia Island, Italy, June 2015,(F. Cicalese, E. Porat, U. Vaccaro, editors).LNCS 9133 pp. 396-409. 


262. D. Amar, D. Yekutieli, A. Maron-Katz, T. Hendler and R. Shamir (2015) "A hierarchical Bayesian model for flexible module discovery in three-way time-series data". Bioinformatics, doi: 


261. Y. Orenstein and R. Shamir (2015) "HTS-IBIS: fast and accurate inference of binding site motifs from HT-SELEX data". bioRxiv, doi: 


260. YY. Goldschmidt, E. Yurkovsky, A. Reif, R. Rosner, A. Akiva and I. Nachman (2015) "Control of Relative Timing and Stoichiometry by a Master Regulator". PLoS One, 10(5): e0127339. doi:10.1371/ journal.pone.0127339. 


259. A. Diament, T. Tuller (2015) "Improving 3D Genome Reconstructions Using Orthologous and Functional Constraints". PLOS Computational Biology, DOI:10.1371/journal.pcbi.1004298. 


258. I. Ben-Bassat and B. Chor (2014) "String Graph Construction Using Incremental Hashing", Bioinformatics, doi: 10.1093/bioinformatics/btu578. 


257. D. Burstein,S. Satanower, M. Simovitch, Y. Belnik, M. Zehavi, G. Yerushalmi,S. Ben-Aroya, T. Pupko, E. Banin (2015) Novel Type III Effectors in Pseudomonas aeruginosa. mBio, 6(2):e00161-15, doi:10.1128/mBio.00161-15. 


256. Y. Silberberg, M. Kupiec, R. Sharan (2014) A Method for Predicting Protein-Protein Interaction Types. PLoS ONE, Vol 9, Issue 3, e90904. 


255. D. S Park, Y. Baran, F. Hormozdiari, C. Eng, D.G. Torgerson, E.G. Burchard, N. Zaitlen (2015) PIGS: improved estimates of identity-by-descent probabilities by probabilistic IBD graph sampling. The 10th International Symposium on Bioinformatics Research and Applications (ISBRA 2014), BMC Bioinformatics 2015, 16(Suppl 5):S9. 


254. A. Wagner, N. Cohen, T. Kelder, U. Amit, E. Liebman, D.M. Steinberg, M. Radonjic & E. Ruppin (2015) Drugs that reverse disease transcriptomic signatures are more effective in a mouse model of dyslipidemia. Molecular Systems Biology, 11: 791, DOI 10.15252/msb.20145486. 


253. D. Amar, I. Frades, T. Diels, D. Zaltzman, N. Ghatan, P. E. Hedley, E. Alexandersson, O. Tzfadia and R. Shamir (2015) The MORPH-R web server and software tool for predicting missing genes in biological pathways. Physiologia Plantarum, doi:10.1111/ppl.12326, 2015.


252. A. Narunsky, H. Ashkenazy, R. Kolodny, N. Ben-Tal (2015) Using ConTemplate and the PDB to explore conformational space: on the detection of rare protein conformations. BMC Bioinformatics 16(Suppl 3):A3. 


251. Y. Oren, M.B. Smith, N.I. Johns, M. Kaplan Zeevi, D. Biran, E.Z. Ron, J. Corander, H.H. Wang, E.J. Alm, and T. Pupko (2014) Transfer of noncoding DNA drives regulatory rewiring in bacteria. PNAS, vol. 111 no. 45, 16112-16117. 


250. H. Ashkenazy, O. Cohen, T. Pupko, and D. Huchon (2014) Indel reliability in indel-based phylogenetic inference. Genome Biol Evol, doi: 10.1093/gbe/evu252Fir. 


249. S. Molshanski-Mor, I. Yosef, R. Kiro, R. Edgar, M. Manor, M. Gershovits, M. Laserson, T. Pupko, and U. Qimron (2014) Revealing bacterial targets of growth inhibitors encoded by bacteriophage T7. PNAS, vol. 111 no. 52 18715-18720. 


248. M. Pour,I. Pilzer, R. Rosner, Z.D. Smith, A. Meissner & I. Nachman (2015) Epigenetic predisposition to reprogramming fates in somatic cells. EMBO Reports, 19 Jan 2015, doi: 10.15252/embr.201439264. 


247. DM. Behar, M. Metspalu, Y. Baran, NM. Kopelman,......S. Rosset, E. al (2013) No evidence from genome-wide data of a Khazar origin for the Ashkenazi Jews. Hum Biol. 85(6):859-900. 


246. E. Levy Karin, E. Susko and T. Pupko (2014) Alignment errors strongly impact likelihood-based tests for comparing topologies. Molecular Biology and Evolution, 31:3057-3067. 


245. A. Brodt , M. Botzman, E. David, I. Gat-Viks (2014) Dissecting dynamic genetic variation that controls temporal gene response in yeast. PLoS Comput Biol. 4;10(12):e1003984. doi: 10.1371/journal.pcbi.1003984. 


244. A. Diament, R. Y. Pinter & T. Tuller(2014) Three-dimensional eukaryotic genomic organization is strongly correlated with codon usage expression and function. Nature Communications, 5:5876, DOI: 10.1038/ncomms6876.


243. D. Amar, I. Frades, A. Danek, T. Goldberg , S.K. Sharma, P.E. Hedley, E. Proux-Wera, E. Andreasson, R. Shamir, O. Tzfadia, E. Alexandersson (2014) Evaluation and integration of functional annotation pipelines for newly sequenced organisms: the potato genome as a test case. BMC Plant Biology, 5;14(1):329. 


242. H. Zur and T. Tuller (2014) Exploiting Hidden Information Interleaved in the Redundancy of the Genetic Code without Prior Knowledge. Bioinformatics,doi:10.1093/bioinformatics/btu797. 


241. D. Golan, E. S. Lander and S. Rosset (2014) Measuring missing heritability: Inferring the contribution of common variants. PNAS November 2014, doi:10.1073/pnas.1419064111. 


240. A. Rubinstein, B. Chor (2014) Computational Thinking in Life Science Education. PLoS Comput Biol 10(11): e1003897. doi:10.1371/journal.pcbi.1003897. 


239. R. Rozov, R. Shamir and E. Halperin (2014) Fast lossless compression via cascading Bloom filters. BMC Bioinformatics, 15(Suppl 9):S7. 


238. D. Golan and S. Rosset(2014) Effective Genetic-Risk Prediction Using Mixed Models. The American Journal of Human Genetics, 95, 383-393. 


237. L. Jerby-Arnon, N. Pfetzer, Y. Y. Waldman, L. McGarry, D. James, E. Shanks, B. Seashore-Ludlow, A. Weinstock, T. Geiger, P. A. Clemons, E. Gottlieb, and E. Ruppin(2014) Predicting Cancer-Specific Vulnerability via Data-Driven Detection of Synthetic Lethality. Cell, 158, 1199-1209. 


236. K. Yizhak, S.E. Le Dévédec, V.M. Rogkoti, F. Baenke, V.C. de Boer, C. Frezza, A. Schulze, B. van de Water and E. Ruppin (2014) A computational study of the Warburg effect identifies metabolic targets inhibiting cancer migration. Molecular Systems Biology, 10: 744, doi: 10.15252/msb.20134993. 


235. G. Fuchs, D. Hollander, Y. Voichek, G. Ast and M. Oren (2014) Co-transcriptional histone H2B monoubiquitylation is tightly coupled with RNA polymerase II elongation rate. Genome Research, doi:10.1101/gr.176487.114.


234. A. Thévenin, L. Ein-Dor, M. Ozery-Flato and R. Shamir (2014) Functional gene groups are concentrated within chromosomes, among chromosomes and in the nuclear space of the human genome. Nucleic Acids Research, doi: 10.1093/nar/gku667. 


233. D. Shem-Tov and E. Halperin (2014) Historical Pedigree Reconstruction from Extant Populations Using PArtitioning of REl- atives. PLoS Comput Bio, l 10(6): e1003610. doi:10.1371/journal.pcbi.1003610, 2014. 


232. Y. Arkin, E. Rahmani, M. E. Kleber, R. Laaksonen, W. Mrz and E. Halperin (2014) EPIQ efficient detection of SNPSNP epistatic interactions for quantitative traits. Bioinformatics, 30 (12): i19-i25, 2014. 


231. I. Eskin, F. Hormozdiari, L. Conde, C. Skibola, J. Riby, E. Eskin and E. Halperin (2013) eALPS: Estimating Abundance Levels in Pooled Sequencing Using Available Genotyping Data. Journal of Computational Biology, 20(11):861-77 (Special issue of RECOMB, 2013). 


230. R. Ronen, N. Udpa, E. Halperin and V. Bafna (2013) Learning Natural Selection from the Site Frequency Spectrum. Genetics. July;194(3):769-79, 2013. 


229. I. Yofe, Z. Zafrir, R. Blau, M. Schuldiner, T. Tuller, E. Shapiro, T. Ben-Yehezkel (2014) Accurate, Model-Based Tuning of Synthetic Gene Expression Using Introns in S. cerevisiae. PLoS Genetics, Vol. 10, Issue 6, e1004407. 


228. Z. Altboum, Y. Steuerman, E. David, Z. Barnett-Itzhaki, L. Valadarsky, H. Keren-Shaul, T. Meningher, E. Mendelson, M. Mandelboim, I. Gat-Viks and I. Amit, (2014). Digital cell quantification identifies global immune cell dynamics during influenza infection. Molecular Systems Biology, 10(2):720. DOI:10.1002/msb.134947. 


227. R. Sabi and T. Tuller(2014) Modelling the Efficiency of Codon-tRNA Interactions Based on Codon Usage Bias. DNA Research, pp. 1-15, doi:10.1093/dnares/dsu017. 


226. S. Kaufman and Saharon Rosset (2014) Exploiting population samples to enhance genome-wide association studies of disease. Genetics, vol. 197 no. 1, 337-349. 


225. G. Daras, S. Rigas, D. Tsitsekian, H. Zur, T. Tuller and P. Hatzopoulos (2014) Alternative transcription initiation and the AUG context configuration control dual organellar targeting and functional competence of Arabidopsis Lon1 protease. Mol. Plant, doi: 10.1093/mp/ssu030. 


224. A. Mazza, I. Gat-Viks, H. Farhan and R. Sharan (2014) A Minimum-Labeling Approach for Reconstructing Protein Networks across Multiple Conditions. Conference proceedings: Workshop on Algorithms in Bioinformatics (WABI), pages 33-44, 2013. 


223. A. Mazza, I. Gat-Viks, H. Farhan and and R. Sharan (2014) A minimum-labeling approach for reconstructing protein networks across multiple conditions. Algorithms Mol. Biol.9;9(1), doi: 10.1186/1748-7188-9-1. 


222. D. Silverbush and R. Sharan (2014) Network orientation via shortest paths. Bioinformatics,doi:10.1093/bioinformatics/btu043. 


221. A. Mazza, I. Gat-Viks, R. Sharan (2014) Elucidating Influenza Inhibition Pathways via Network Reconstruction. J. Comput. Biol. Vol 21, DOI: 10.1089/cmb.2013.0147. 


220. I. Gat-Viks, N. Chevrier, R. Wilentzik, T. Eisenhaure, R. Raychowdhury, Y. Steuerman, A. K. Shalek, N. Hacohen, I. Amit and A. Regev (2013) Deciphering molecular circuits from genetic variation underlying transcriptional responsiveness to stimuli. Nature Biotechnology, 31, 342-349. 


219. Y. Orenstein and R. Shamir (2014) A comparative analysis of transcription factor binding models learned from PBM, HT-SELEX and ChIP data. Nucleic Acids Research, doi:10.1093/nar/gku117. 


218. D. Amar and R. Shamir (2014) Constructing module maps for integrated analysis of heterogeneous biological networks. Nucleic Acids Research, doi:10.1093/nar/gku102. 


217. E. Persi, D. Horn (2013) Systematic Analysis of Compositional Order of Proteins Reveals New Characteristics of Biological Functions and a Universal Correlate of Macroevolution. PLoS Comput Biol 9(11): e1003346. doi:10.1371/journal.pcbi.1003346. 


216. A. Wagner, R. Zarecki, L. Reshef, C. Gochev, R. Sorek, U. Gophna, and E. Ruppin (2013) "Computational evaluation of cellular metabolic costs successfully predicts genes whose expression is deleterious". PNAS, org/cgi/doi/10.1073/pnas.1312361110 . 


215. O. Navon, J. Hoon Su, B. Han, L. Conde, P. Bracci, J. Riby, C. F. Skibola, E. Eskin, E. Halperin (2013) "Rare Variant Association Testing under Low-Coverage Sequencing". Genetics, 194(3):769-79. 


214. S.L. Slager, C.F. Skibola, M.C. Di Bernardo...., E. Halperin,...N.J. Camp, J. B.Weinberg, E. Matutes, N.E. Caporaso....J.R. Cerhan, D. Catovsky and R.S. Houlston (2013) "Common variation at 6p21.31 (BAK1) influences the risk of chronic lymphocytic leukemia". Blood, doi:10.1182/blood-2012-03-413591. (PDF) 


213. Z. Wang, F. Hormozdiari, W.-Y. Yang, E.Halperin, and E. Eskin (2013) "CNVeM: Copy Number Variation Detection Using Uncertainty of Read Mapping". Jornal of Computational Biology, Vol. 20, No. 3, 224-236. 


212. B. Pasaniuc,S. Sankararaman, D. G. Torgerson, C. Gignoux.... and E. Halperin (2013) "Analysis of Latino populations from GALA and MEC studies reveals genomic loci with biased local ancestry estimation". Bioinformatics, Vol. 29 no. 11, 1407-1415. 


211. W.-Y. Yang, J. Novembre, E. Eskin & E. Halperin (2013) "A model-based approach for analysis of spatial structure in genetic data". Nature Genetics, doi:10.1038/ng.2285. 


210. K. Yizhak, O. Gabay, H. Cohen & E. Ruppin(2013) "Model-based identification of drug targets that revert disrupted metabolism and its application to ageing", Nature Communications, 4:2632. 


209. Zur, H. and Tuller, T. (2013) "Transcript features alone enable accurate prediction and understanding of gene expression in S. cerevisiae", BMC Bioinformatics 2013, doi:10.1186/1471-2105-14-S15-S1. 


208. G.H. Romano, Y. Harari , T. Yehuda ,A. Podhorzer , L. Rubinstein , R. Shamir , A. Gottlieb , Y. Silberberg ,D. Pe'er , E. Ruppin , R. Sharan , M. Kupiec (2013) Environmental Stresses Disrupt Telomere Length Homeostasis. PLoS Genet. 9(9):e1003721. doi: 10.1371/journal.pgen.1003721. Epub 2013 Sep 5. 


207. R.E. Bell, M. Khaled, D. Netanely, S. Schubert, T. Golan, A. Buxbaum, M. M. Janas, B. Postolsky, M.S. Goldberg, R. Shamir, C. Levy(2013)"Transcription Factor/microRNA Axis Blocks Melanoma Invasion Program by miR-211 Targeting NUAK1". Journal of Investigative Dermatology, doi: 10.1038/jid.2013.340. 


206. MA. Oberhardt, K. Yizhak, E. Ruppin (2013)"Metabolically re-modeling the drug pipeline". Current Opinion in Pharmacology, 13:1-8. 


205. A. Rubinstein, O. Hazan, B. Chor, R. Y. Pinter and Y. Kassir (2013)"The effective application of a discrete transition model to explore cell-cycle regulation in yeast". BMC Research Notes 2013, 6:311. 


204. T. Ben-Yehezkel, H. Zur, et al.(2013)"Mapping the Translation Initiation Landscape of an S. cerevisiae Gene Using Fluorescent Proteins." Genomics. 


203. H. Zur, T. Tuller (2013) New Universal Rules of Eukaryotic Translation Initiation Fidelity. PLoS Comput Biol 9(7): e1003136. doi:10.1371/journal.pcbi.1003136. 


202. D. Golan and P. Medvedev (2013) Using state machines to model the Ion Torrent sequencing process and to improve read error rates. Bioinformatics, Vol. 29, ISMB/ECCB pages i344-i351. 


201. Y. Orenstein and R.Shamir (2013) Design of shortest double-stranded DNA sequences covering all k-mers with applications to protein-binding microarrays and synthetic enhancers. Bioinformatics, Vol. 29 ISMB/ECCB, pages i71-i79. 


200. A. Mazza, I.G. Viks, H. Farhan, and R. Sharan(2013) A minimum-labeling approach for reconstructing protein networks across multiple conditions. In Proc. Algorithms in Bioinformatics. WABI 2013. Lecture Notes in Computer Science, vol 8126. Springer, Berlin, Heidelberg.


199. G. Wainreb, L. Wolf, H. Ashkenazy, Y. Dehouck and N. Ben-Tal (2011) Protein stability: a single recorded mutation aids in predicting the effects of other mutations in the same amino acid site. Bioinformatics, 1;27(23):3286-92.  


198. O. Cohen, H. Ashkenazy, E. Levy Karin, D. Burstein and T. Pupko (2013) CoPAP: Coevolution of Presence-Absence Patterns. Nucleic Acid Research, 41 (W1): W232-W237. 


197. G. Celniker, G. Nimrod, H. Ashkenazy, F. Glaser, E. Martz, I. Mayrose, T. Pupko and N. Ben-Tal (2013) ConSurf: Using Evolutionary Data to Raise Testable Hypotheses about Protein Function. Israel Journal of Chemistry, 53(3-4):199-206. 


196. O. Tzfadia, D. Amar, L.M.T. Bradbury, E. T. Wurtzel and R. Shamir (2012) The MORPH Algorithm: Ranking Candidate Genes for Membership in Arabidopsis and Tomato PathwaysC. The Plant Cell, 24(11):4389-406, 2012. 


195. I. Gat-Viks, N. Chevrier, R. Wilentzik, T. Eisenhaure, R. Raychowdhury, Y. Steuerman, A. K. Shalek, N. Hacohen, I. Amit and A.Regev (2013) Deciphering molecular circuits from genetic variation underlying transcriptional responsiveness to stimuli. Nature Biotechnology, doi:10.1038/nbt.2519. 


194. J. Lewin Rukov, R. Wilentzik, I. Jaffe, J. Vinther and N. Shomron (2013) Pharmaco-miR: linking microRNAs and drug effects. Briefings in Bioinformatics, doi:10.1093/bib/bbs082.  


193. T. Ben-Yehezkel, H. Zur, T. Marx, E. Shapiro, T. Tuller (2013) Mapping the translation initiation landscape of an S. cerevisiae gene using fluorescent proteins. Genomics, doi. org / 10.1016 / j.ygeno.2013.05.003. 


192. Y. Baran, I. Quintela, Á. Carracedo, B. Pasaniuc, E. Halperin (2013) Enhanced Localization of Genetic Samples through Linkage-Disequilibrium Correction. The American Journal of Human Genetics, Vol. 92, Issue 6, pp. 882-894.  


191. Y. Orenstein, E. Mick and R. Shamir (2013) RAP: Accurate and fast motif finding based on protein binding microarray data. Journal of Computational Biology, Vol. 20, No. 5: 375-382.  


190. Gelfman S, Cohen N, Yearim A, and Ast G. (2013) DNA-methylation effect on co-transcriptional splicing is dependent on GC-architecture of the exon-intron structure. Genome Res. doi:10.1101/gr.143503.112 . 


189. Ramalho RF, Gelfman S, de Souza JE, Ast G, de Souza SJ, Meyer D. (2013) Testing for Natural Selection in Human Exonic Splicing Regulators Associated with Evolutionary Rate Shifts. J Mol Evol. DOI 10.1007/s00239-013-9555-2 .  


188. M. S. Bansal, G. Banay, J. P. Gogarten, R. Shamir.(2011) Detecting Highways of Horizontal Gene Transfer. Bioinformatics 29(5): 571-579. 


187. M. S. Bansal, G. Banay, T. J. Harlow, J. P. Gogarten, R. Shamir (2013) Systematic Inference of Highways of Horizontal Gene Transfer in Prokaryotes. Bioinformatics 29(5): 571-579. 


186. Amar, D., Safer, H., Shamir, R. (2013) Dissection of Regulatory Networks that Are Altered in Disease via Differential Co-expression. Plos Computational Biology. Vol 9, No. 3.e1002955, doi:10.1371/journal.pcbi.1002955. 


185. Efros A., Halperin E., (2012) Haplotype reconstruction using perfect phylogeny and sequence dataBMC Bioinformatics. 13(Suppl 6): S3. 


184. Topfer A., Zagordi O., Prabhakaran S., Roth V., Halperin E., Beerenwinkel N., (2013) Probabilistic inference of viral quasispecies subject to recombination. Journal of Computational Biology, 20(2):113-23. 


183. N. Atias and R. Sharan. iPoint: an integer programming based algorithm for inferring protein subnetworks (2013) Mol. BioSyst., DOI: 10.1039/C3MB25432A. 


182. E. Cohen and B. Chor. (2012) Detecting Phylogenetic Signals in Eukaryotic Whole Genome Sequences. Journal of Computational Biology, 19(8): 945-956. 


181. Goldstein I., Yizhak K., Madar S., Goldfinger N., Ruppin E., Rotter V. (2013) p53 promotes the expression of gluconeogenesis-related genes and enhances hepatic glucose production. Cancer & Metabolism, 1:9, DOI: 10.1186/2049-3002-1-9. 


180. M.T. Weirauch, A. Cote, R. Norel, M. Annala, Y. Zhao, T.R. Riley, J. Saez-Rodriguez, T. Cokelaer, A. Vedenko, S. Talukder, DREAM5 Consortium (including Y. Orenstein, C. Linhart, R. Shamir), H.J. Bussemaker, Q.D. Morris, M.L. Bulyk, G. Stolovitzky & T.R. Hughes (2013) Evaluation of methods for modeling transcription factor sequence specificity, Nature Biotechnology, doi:10.1038/nbt.2486, 2013. 


179. M. Gymrek, A. L. McGuire, D. Golan, E. Halperin, Y. Erlich (2013) Identifying Personal Genomes by Surname Inference. Science, vol. 339, 321, DOI: 10.1126/science.1229566. 


178. Cohen, O., Ashkenazy, H., Burstein, D., and Pupko, T. (2012) Uncovering the co-evolutionary network among prokaryotic genes. Bioinformatics. 28 ECCB 2012:i389-i394.


177. Rozov R., Halperin E., Shamir R. (2012) MGMR: leveraging RNA-Seq population data to optimize expression estimation. BMC Bioinformatics 2012, 13(Suppl 6):S2.


176. Baran Y., Halperin E. (2012) Joint analysis of multiple metagenomic samples. PLoS Comput Biol. 8(2):e1002373.


175. Baran Y, Pasaniuc B, Sankararaman S, Torgerson DG, Gignoux C, Eng C, Rodriguez-Cintron W, Chapela R, Ford JG, Avila PC, Rodriguez-Santana J, Burchard EG, Halperin E. (2012) Fast and accurate inference of local ancestry in Latino populations. Bioinformatics. 15;28(10):1359-67. 


174. E. Yurkovsky, I. Nachman (2013) Event timing at the single cell level. Brief Funct Genomics, 12(2):90-8, 2013. 


173. D. Salomon, D. Dar, I. Nachman, G. Sessa. (2012) Expression of Pseudomonas syringae type III effectors in yeast under stress conditions reveals that HopX1 attenuates activation of the high osmolarity glycerol pathway. Microbiology 158(11), pp. 2859-69. 


172. 1000 Genomes Project Consortium, A. GR,..., Y. Baran, E. Halperin, et al. (2012) An integrated map of genetic variation from 1,092 human genomes, Nature, 491, 56-65.


171. Magger O, Waldman YY, Ruppin E, Sharan R (2012) Enhancing the Prioritization of Disease-Causing Genes through Tissue Specific Protein Interaction Networks. PLoS Comput Biol 8(9): e1002690. doi:10.1371/journal.pcbi.1002690.


170. Aidelberg, G., Goldshmidt, Y., Nachman, I. (2012) A Microfluidic Device for Studying Multiple Distinct Strains. J. Vis. Exp. (69), e4257, doi:10.3791/4257. 


169. A.Cohen, L. Ross, I. Nachman, S. Bar-Nun (2012) Aggregation of PolyQ Proteins Is Increased upon Yeast Aging and Affected by Sir2 and Hsf1: Novel Quantitative Biochemical and Microscopic Assays, PloS One, Volume 7, Issue 9, e44785.


168. Lurie-Weinberger ,N,Tuller T, Peeri and Gophna U. (2012) Extensive Inter-Domain Lateral Gene Transfer in the Evolution of the Human Commensal Methanosphaera stadtmanae, Front Genet. 2012; 3: 182. 


167. Orenstein Y, Linhart C, Shamir R (2012) Assessment of Algorithms for Inferring Positional Weight Matrix Motifs of Transcription Factor Binding Sites Using Protein Binding Microarray Data. PLoS ONE 7(9): e46145. doi:10.1371/journal.pone.0046145. 


166. D. Marbach, J. C. Costello, R. Kueffner, N. Vega, R. J. Prill, D. M. Camacho, K. R. Allison, the DREAM5 Consortium (including G. Karlebach, R. Shamir), M. Kellis, J. J. Collins G. Stolovitzky (2012) Wisdom of crowds for robust gene network inference. Nature Methods, 9(8):796-804.


165. Neuman J.A., Isakov O. and Shomron N. (2012) Analysis of insertion-deletion from deep sequencing data: software evaluation for optimal detection. Briefings in Bioinformatics, 2013 Jan;14(1):46-55. doi: 10.1093/bib/bbs013. Epub 2012 Mar 24.


164. Isakov O., Ronen R., Kovarsky J., Gabay A., Gan I., Modai S. and Shomron N. (2012) Novel insight into the non-coding repertoire through deep sequencing analysis. Nuc Acid Res; doi: 10.1093/nar/gks228.


163. A. Ryvkin, H. Ashkenazy, L. Smelyanski, G. Kaplan, O. Penn, Y. Weiss-Ottolenghi, E. Privman, P. B. Ngam, J. E. Woodward, G.D. May, C. Bell, T. Pupko and J. M. Gershoni (2012) Deep panning: steps towards probing the IgOme. PLoS One. 7(8): p. e41469.


162. H. Ashkenazy, O.Penn, A. Doron-Faigenboim, O. Cohen, G. Cannarozzi , O. Zomer and T. Pupko. (2012) FastML: a web server for probabilistic reconstruction of ancestral sequences. Nucleic Acids Res. 40 (Web Server issue):W580-4. 


161. H. Zur and T. Tuller (2012) RFMapp: ribosome flow model applicationBioinformatics, Vol. 28 no. 12, pages 1663–1664.


160. D. Golan, Y. Erlich and S. Rosset (2012) Weighted pooling—practical and cost-effective techniques for pooled high-throughput sequencing, Bioinformatics. Vol. 28 ISMB 2012, pages i197–i206, doi:10.1093/bioinformatics/bts208.


159. M. Amit, M. Donyo, D. Hollander, A. Goren, E.Kim, S. Gelfman, G. Lev-Maor, D. Burstein, S. Schwartz, B. Postolsky, T. Pupko, and G. Ast (2012) Differential GC Content between Exons and Introns Establishes Distinct Strategies of Splice-Site Recognition. Cell Reports 1, 1–14, doi:10.1016/j.celrep.2012.03.013. 


158. D. Golan and S. Rosset (2012) Comment on “The Predictive Capacity of Personal Genome Sequencing”. Science Translational Medicine, Vol 4 Issue 135 135le4. 


157. Turner, D., Amit, S., Chalom, S., Penn, O., Pupko T., Katchman, E., Matus, N., Tellio, H., Katzir, M., Avidor, B. 2012. Emergence of an HIV-1 cluster harboring the major protease L90M mutation among treatment-naive patients in Tel-Aviv, Israel. HIV Medicine  13:202-206. 


156. Privman, E, Penn, O. and Pupko, T. 2012. Improving the performance of positive selection inference by filtering unreliable alignment regions. Mol. Biol. Evol. 29(1):1-5. 


155. Atias, N. and Sharan R. (2012) . Communications of the ACM, vol. 55, no. 5, pp 88-97.


154. M. Gymrek, D. Golan,S. Rosset and Y. Erlich (2012) lobSTR: A short tandem repeat profiler for personal genomes. Genome Research. doi 10.1101/gr.135780.111 Genome Res. 2012. 


153. Y. Silberberg, A. Gottlieb, M. Kupiec, E. Ruppin, and R. Sharan (2012) Large-Scale Elucidation of Drug Response Pathways in HumansJournal of Computational Biology, Vol 19, 2, Pp. 163–174.


152. E. Persi, U. Weingart, S. Freilich and D. Horn (2012) Peptide Markers of Aminoacyl tRNA Synthetases Facilitate Taxa Counting in Metagenomic DataBMC Genomics, 13:65.  


151. Gelfman, S., D. Burstein, O. Penn, A. Savchenko, M. Amit, S. Schwartz, T. Pupko, and G. Ast. (2011) Changes in exon-intron structure during vertebrate evolution affect the splicing pattern of exons. Genome Research. doi:10.1101/gr.119834.110.


150. Freilich S, R. Zarecki, O. Eilam, E. Shtifman Segal, C. S. Henry, M. Kupiec, U. Gophna, R. Sharan & E. Ruppin (2011) Competitive and cooperative metabolic interactions in bacterial communities. Nature Communications, 2:589, doi: 10.1038/ncomms1597.


149. M. N. Lurie-Weinberger, M. Peeri, U. Gophna (2012) Contribution of lateral gene transfer to the gene repertoire of a gut-adapted methanogenGenomics, 99, 52–58.


148. Rubinstein, N.D., Zeevi, D., Oren, Y., Segal, G., and Pupko, T. (2011) The operonic location of auto-transcriptional repressors is highly conserved in bacteria. Mol. Biol. Evol. 28(12):3309-3318.


147. Rubinstein, N.D., Mayrose, I., Doron-Faigenboim, A., and Pupko, T. (2011) Evolutionary models accounting for layers of selection in protein coding genes and their impact on the inference of positive selectionMol. Biol. Evol. 28(12):3297–3308. 2011. 


146. Barzel, A., Privman, E., Peeri, M., Naor, A., Shachar, E., Burstein, D., Lazary, R., Gophna, U., Pupko, T., and Kupiec, M. (2011) Native homing endonucleases can target conserved genes in humans and in animal models. Nucleic Acids Research. 39(15):6646-6659. 


145. K. Yizhak, T. Tuller, B. Papp & E. Ruppin (2011) Metabolic modeling of endosymbiont genome reduction on a temporal scaleMolecular Systems Biology 7:479. 


144. B. Kirkpatrick, E. Halperin and R. M. Karp (2011) Haplotype Inference in Complex Pedigrees. DOI: 10.1089/cmb.2009.0174, pp. 269-280. 


143. E. Halperin et al (2011) Large-scale association analysis identifies 13 new susceptibility loci for coronary artery diseaseNature Genetics ,43, 4.


142. A.Kovacs, N. Ben-Jacob, H. Tayem , E. Halperin , F. A. Iraqi, U. Gophna (2011) Genotype Is a Stronger Determinant than Sex of the Mouse Gut Microbiota. Microb Ecol, 61:423-428. 


141. B. Pasaniuc, N. Zaitlen and E. Halperin (2011) Accurate Estimation of Expression Levels of Homologous Genes in RNA-seq Experiments. Journal of Computational Biology 18, Number, pp. 459-468.


140. D. He, N. Zaitlen, B. Pasaniuc, E. Eskin, E. Halperin (2011) Genotyping common and rare variation using overlapping pool sequencing. BMC Bioinformatics , 12(Suppl 6):S2. 


139. B. Kirkpatrick, S. Cheng Li, R. M. Karp, and E. Halperin (2011) Pedigree Reconstruction Using Identity. V. Bafna and S.C. Sahinalp (Eds.): RECOMB 2011, LNBI 6577, pp. 136-152, 2011.


138. O. Cohen and T. Pupko (2011) Inference of Gain and Loss Events from Phyletic Patterns Using Stochastic Mapping and Maximum Parsimony—A Simulation Study. Genome Biol. Evol. 3:1265–1275. doi:10.1093/gbe/evr101.


137. D. Golan and S. Rosset (2011)Accurate estimation of heritability in genome wide studies using random effects models. ISMB Vol. 27 2011, pages i317–i323 doi:10.1093/bioinformatics/btr219.


136. Waldman Y.Y., Tuller T., Keinan A., Ruppin E. (2011) Selection for translation efficiency on synonymous polymorphisms in recent human evolution. Genome Biol Evol. 3, 749-761.


135. C. Frezza, L. Zheng, O. Folger, K. N. Rajagopalan, E. D. MacKenzie, L. Jerby, M. Micaroni, B. Chaneton, J. Adam, A. Hedley, G. Kalna, I. P. M. Tomlinson, P. J. Pollard, D. G. Watson, R. J. Deberardinis, T. Shlomi, E. Ruppin, & E. Gottlieb (2011) Haem oxygenase is synthetically lethal with the tumour suppressor fumarate hydrataseNature, doi:10.1038/nature10363. 


134. O. Isakov, S. Modai, and N. Shomron (2011) Pathogen Detection Using Short-RNA Deep Sequencing Subtraction and Assembly.  Bioinformatics, doi: 10.1093/bioinformatics/btr349, Jun. 2011. 


133. Shcushan, M., Landau, M., Padan, E., and Ben-Tal., N. (2011) Two Conflicting NHE1 Model Structures: Compatibility with Experimental Data and Implications for the Transport Mechanism. J Biological Chemistry, vol. 286, no. 21, p. le9, May 27, 2011. 


132. Cohen, O., and Pupko, T. (2011) The complexity hypothesis revisited: connectivity rather than function constitutes a barrier to horizontal gene transfer. Mol. Biol. Evol. 28(4):1481-1489.


131. Cohen, O., Ashkenazy, H., Belinky, F., Huchon, D., and Pupko, T. (2010) GLOOME: gain loss mapping engine. Bioinformatics 26(22):2914-2915. 


130. Loe-Mie, Y., Lepagnol-Bestel, A.D., Maussion, G., Doron-Faigenboim, A., Imbeaud, S., Delacroix, H., Aggerbeck, L., Pupko, T., Gorwood, P., Simonneau, M., and Moalic, J.M. (2010) SMARCA2 and other genome-wide supported schizophrenia-associated genes: regulation by REST/NRSF, network organization and primate-specific evolution. Human Molecular Genetics 19(14):2841-2857. 


129. Penn, O., Privman, E., Landan, G., Graur, D., and Pupko, T. (2010) An alignment confidence score capturing robustness to guide-tree uncertainty Mol. Biol. Evol. 27(8):1759-1767.


128. U. Weingart , E. Persi , U. Gophna and D. Horn (2010) Deriving enzymatic and taxonomic signatures of metagenomes from short read data. BMC Bioinformatics, 11:390 doi:10.1186/1471-2105-11-390.


127 .Schwartz S, Oren R, Ast G (2011) Detection and Removal of Biases in the Analysis of Next-Generation Sequencing Reads. PLoS ONE 6(1): e16685. doi:10.1371/journal.pone.0016685. 


126 .Z.D. Smith, I. Nachman, A. Regev, A. Meissner (2010) Dynamic single cell imaging of direct reprogramming reveals an early specifying event. Nature Biotechnology 28(5), 521 – 526.


125 .N. Atias and R. Sharan (2011) An Algorithmic Framework for Predicting Side Effects of Drugs. Journal of Computational Biology. March 2011, 18(3): 207-218. 


124 L. Perlman, A. Gottlieb, N. Atias, E. Ruppin and R. Sharan (2011) Combining drug and gene similarity measures for drug-target elucidation. Journal of Computational Biology, 18(2): 133-145.


123. T. Elkan-Miller, I. Ulitsky, R. Hertzano, A. Rudnicki, A. A. Dror, D. R. Lenz, R. Elkon, M. Irmler, J. Beckers, R. Shamir, K. B. Avraham (2011) Integration of Transcriptomics, Proteomics, and MicroRNA Analyses Reveals Novel MicroRNA Regulation of Targets in the Mammalian Inner Ear. Plos One, Volume 6 Issue 4 e18195..


122. Schushan, M. and Ben-Tal, N. Chapter 17: Modeling and validation of transmembrane protein structures. in “Introduction to Protein Structure Prediction: Methods and Algorithms” (2010) John Wiley and Sons, New Jersey, Huzefa Rangwala and George Karypis (Eds), pp 369-402.


121. S. Bunimovich-Mendrazitsky, J. C. Gluckman, J. Chaskalovic (2011) A mathematical model of combined bacillus Calmette-Guerin (BCG) and interleukin (IL)-2 immunotherapy of superficial bladder cancer. Journal of Theoretical Biology 277, 27–40.


120. S. Bunimovich-Mendrazitsky, J. C. Gluckman, J. Chaskalovic (2011) A mathematical model of combined bacillus Calmette-Guerin (BCG) and interleukin (IL)-2 immunotherapy of superficial bladder cancer. Journal of Theoretical Biology 277, 27–40.


119. H. Sharon, D. Amar, E. Levdansky, G. Mircus, Y. Shadkchan, R. Shamir, N. Osherov (2011) PrtT-Regulated Proteins Secreted by Aspergillus fumigatus Activate MAPK Signaling in Exposed A549 Lung Cells Leading to Necrotic Cell Death. PLoS One, 6, Issue 3, e17509. 


118.Tuller T., Felder Y., Kupiec M. (2010) Discovering local patterns of co - evolution: computational aspects and biological examples. BMC Bioinformatics, 11:43, 1471-2105.


117.Tuller T., Birin H., Gophna U., Kupiec M. and Ruppin E. ( 2010) Reconstructing ancestral gene content by coevolution, Genome Research. 20: 122-132.


116.Gurevich M., Tuller T., Rubinstein U., Or-Bach R. and Achiron A. (2009) Prediction of acute multiple sclerosis relapses by transcription levels of peripheral blood cells. BMC Medical Genomics 2:46.


115.Benyamini T., Folger O., Ruppin E. and Shlomi T. (2010) Flux balance analysis accounting for metabolite dilution. Genome Biology, 11:R43. 


114.Jerby L., Shlomi T. and Ruppin E. (2010) Computational reconstruction of tissue-specific metabolic models: application to human liver metabolism. Molecular Systems Biology 6:401.


113.Ulitsky I., Krishnamurthy A., Karp R. M., AND Shamir R. (2010) DEGAS: De Novo Discovery of Dysregulated Pathways in Human Diseases. PLoS One , 5 (10) e13367. 


112. Belinky F., Cohen O., and Huchon D. (2010) Large-Scale Parsimony Analysis of Metazoan Indels in Protein-Coding Genes. Mol. Biol. Evol. 27(2):441-451. 


111. Freilich S, Kreimer A, Borenstein E, Gophna U, Sharan R, et al. (2010) Decoupling Environment-Dependent and Independent Genetic Robustness across Bacterial Species. PLoS Comput Biol 6(2): e1000690. doi:10.1371/journal.pcbi.1000690.


110. Stern A. , Mayrose I., Penn O., Shaul S., Gophna U., and Pupko T.(2010) An Evolutionary Analysis of Lateral Gene Transfer in Thymidylate Synthase Enzymes. Syst. Biol. 59(2):212-225.


109. Penn O., Privman E., Ashkenazy H., Landan G., Graur D. and Pupko T. (2010) GUIDANCE: a web server for assessing alignment confidence scores. Nucleic Acids Research, 2010, 1-6.


108. A. Paz, Z. Brownstein, Y. Ber, S. Bialik, E. David, D. Sagir, I. Ulitsky, R. Elkon, A. Kimchi, K. B. Avraham, Y. Shiloh and R. Shamir (2011) SPIKE: a database of highly curated human signaling pathways. Nucleic Acids Research. vol. 39, Database issue D793-D799, 2011.


107. L.C. Laurent, I. Ulitsky, I.Slavin, H. Tran, A. Schork, R. Morey, C. Lynch, J.V. Harness, S. Lee, M.J. Barrero, S. Ku, M. Martynova, R. Semechkin, V. Galat, J. Gottesfeld, J.C. Izpisua Belmonte, C. Murry, H. S. Keirstead, H.-S. Park, U. Schmidt, A.L. Laslett, F.-J. Muller, C. M. Nievergelt, . Shamir and J. F. Loring (2011) Dynamic Changes in the Copy Number of Pluripotency and Cell Proliferation Genes in Human ESCs and iPSCs during Reprogramming and Time in Culture. Cell Stem Cell. doi: 10.1016/j.stem.2010.12.003,2011.


106. R. Chaudhary, M. S. Bansal, A. Wehe, D. Fernández-Baca, Oliver Eulenstein (2010). iGTP: A software application for large-scale gene tree parsimony analysis BMC Bioinformatics 2010, 11:574.


105. M. Llorian, S. Schwartz, T. A. Clark, D. Hollander, L.-Y. Tan, R. Spellman, A. Gordon, A. C. Schweitzer, P. de la Grange, G. Ast & C. W. J. Smith (2010) Position-dependent alternative splicing activity revealed by global profiling of alternative splicing events regulated by PTB. Structural & Molecular Biology, doi:10.1038/nsmb.1881.


104. Pasaniuc B., Avinery R., Gur T., Skibola C.F., Bracci P.M., and Halperin E. (2010) A Generic Coalescent-based Framework for the Selection of a Reference Panel for ImputationGenet. Epidemiol., DOI: 10.1002/gepi.20505.


103.O. Rechavi, M. Kalman, Y. Fang, H. Vernitsky, J. Jacob-Hirsch, L. J Foster, Y. Kloog & I. Goldstein (2010) Trans-SILAC: sorting out the non-cell-autonomous proteome, Nature, doi:10.1038/nmeth.1513.


102.Schwartz S. and Ast G. (2010) Chromatin density and splicing destiny: on the cross-talk between chromatin structure and splicing. The EMBO Journal, 29, 1629 - 1636 doi:10.1038/emboj.2010.71.


101.Mukul S. Bansal, J. Peter Gogarten, and Ron Shamir (2010) Detecting Highways of Horizontal Gene Transfer. 8th Annual RECOMB Comparative Genomics Workshop (RECOMB-CG 2010), LNCS 6398: 109-120.


100. I. Ulitsky and R. Shamir. (2009) Identifying functional modules using expression profiles and confidence-scored protein interactions. Bioinformatics Vol. 25 no. 9 pages 1158-1164 (2009).


99. O. Davidovich, G. Kimmel, E. Halperin, R. Shamir (2009) Increasing the Power of Association Studies by Imputation-based Sparse Tag SNP Selection. Communications in Information and Systems 9 (3) 269-282 (2009) .


98. S. Bruckner, F. Hüffner, R. M. Karp, R. Shamir, R. Sharan (2009) Torque: topology-free querying of protein interaction networks. Nucleic Acids Research, doi: 10.1093/nar/gkp474.


97. I. Ulitsky, N.J. Krogan and R. Shamir (2009) Towards accurate imputation of quantitative genetic interactions. Genome Biology, Volume 10:R140 2009. 


96. I. Ulitsky, A. Maron-Katz, S. Shavit, D. Sagir, C. Linhart, R. Elkon, A. Tanay, R. Sharan, Y. Shiloh, R. Shamir (2010) Expander: from expression microarrays to networks and functions. Nature Protocols, Vol 5, pp 303 - 322, 2010.


95.   G. H. Romano, Y. Gurvich, O. Lavi, I. Ulitsky, R. Shamir, M. Kupiec (2010) Different sets of QTLs influence fitness variation in yeast. Molecular Systems Biology 6:346, doi:10.1038/msb.2010.1, 2010.


94. Bruckner, S., Hüffner, F., Karp, R.M., Shamir, R., Sharan, R. (2010) Topology-free querying of protein interaction networks. Journal of Computational Biology , 17 (3), pp. 237-252 (2010). 


93. P.S. Aguilar, F. Fröhlich, M. Rehman, M. Shales, I. Ulitsky, A. Olivera-Couto, H. Braberg, R. Shamir, P. Walter, M. Mann, C.S. Ejsing, N.J. Krogan, T.C. Walther (2010) A plasma-membrane E-MAP reveals links of the eisosome with sphingolipid metabolism and endosomal trafficking. Nature Structural and Molecular Biology, Vol. 17 no. 7, pp 901-909 (2010). 


92. Bansal MS, Shamir R. (2010) A Note on the Fixed Parameter Tractability of the Gene-Duplication Problem. IEEE/ACM Transactions on Computational Biology and Bioinformatics, August 20, 2010.


91.   R. Ronen, I. Gan, S. Modai, A. Sukacheov, G. Dror, E. Halperin, N. Shomron. (2010) miRNkey: a software for microRNA deep sequencing analysis. Bioinformatics, published August 27, 2010. 


90. I. Ulitsky, L. C. Laurent, R. Shamir (2010) Towards computational prediction of microRNA function and activity. Nucleic Acids Research, vol. 38, 15, pp 160. 


89. Ziv-Ukelson M, Gat-Viks I, Wexler Y, Shamir R (2010) A Faster Algorithm for Simultaneous Alignment and Folding of RNA. J Comput Biol. 2010 Jul 22. PMID: 20649420.


88.  Lucia Conde, Eran Halperin, Nicholas K Akers et al (2010) Genome-wide association study of follicular lymphoma identifies a risk locus at 6p21.32. Nature Genetics. vol. 42, no. 8, 2010 doi:10.1038/ng.626 


87. Schushan M, Barkan Y, Haliloglu T, Ben-Tal N .  Proc Natl Acad Sci U S A. (2010) C(alpha)-trace model of the transmembrane domain of human copper transporter 1, motion and functional implicationsProc Natl Acad Sci U S A. 2010 Jun 15;107(24):10908-13 . 


86: Keren Yizhak, Tomer Benyamini, Wolfram Liebermeister, Eytan Ruppin, Tomer Shlomi (2010) Integrating quantitative proteomics and metabolomics with a genome-scale metabolic network model. Bioinformatics, 26, 255–260. 


85. Mor N. Lurie-Weinberger, Laura Gomez-Valero, Nathalie Merault, Gernot Glockner, Carmen Buchrieser, Uri Gophna (2010) The origins of eukaryotic-like proteins in Legionella pneumophila. International Journal of Medical Microbiology,  2010 Nov;300(7):470-81. doi: 10.1016/j.ijmm.2010.04.016. Epub 2010 May 26.


84. Waldman Y.Y., Tuller T., Shlomi T., Sharan R., Ruppin E. (2010) Translation efficiency in humans: tissue specificity, global optimization and differences between developmental stages. Nucleic Acids Res. 38, 2964-2674 


83. Tomer Benyamini , Ori Folger Eytan Ruppin and Tomer Shlomi (2010) Flux balance analysis accounting for metabolite dilutionGenome Biology 2010, 11:R43doi:10.1186/gb-2010-11-4-r43. 


82. Kalman, M. and Ben-Tal, N. (2010) Quality assessment of protein model-structures using evolutionary conservation. Bioinformatics 26(10):1299-1307. 


81. G. Karlebach, R. Shamir (2010) Minimally perturbing a gene regulatory network to avoid a disease phenotype: the glioma network as a test case. BMC Systems Biology , 4:15 doi:10.1186/1752-0509-4-15. 


80. Nimrod G, Schushan M, Szilagyi A, Leslie C, Ben-Tal N. (2010) iDBPs: a web server for the identification of DNA binding proteins. Bioinformatics. 2010 Mar 1;26(5):692-3. 


79. Mukul S Bansal, J G Burleigh, Oliver Eulenstein, and David Fernandez-Baca. (2010) Robinson-Foulds Supertrees . Algorithms for Molecular Biology, 5:18. 


78. Tuller T., Waldman Y.Y., Kupiec M., Ruppin E. (2010) Translation efficiency is determined by both codon bias and folding energy. Proc. Natl. Acad. Sci. USA. 107, 3645-3650. 


77. Mukul S. Bansal, J. Gordon Burleigh, Oliver Eulenstein (2010) Efficient genome-scale phylogenetic analysis under the duplication-loss and deep coalescence cost models. Asia-pacific Bioinformatics Conference, BMC Bioinformatics 2010, 11(Suppl 1):S4 2. 


76. Weingart U., Lavi Y., and Horn D. (2009) Data mining of enzymes using specific peptides. BMC Bioinformatics, 10:446 doi:10.1186/1471-2105-10-446. 


75. Cohen, O., and Pupko T. (2010) Inference and characterization of horizontally transferred gene families using stochastic mapping. Mol. Biol. Evol. 27(3):703-713. 


74. M. Schushan, M. Xiang, P. Bogomiakov, E. Padan, R. Rao and N. Ben-Tal, (2010) Model-Guided Mutagenesis Drives Functional Studies of Human NHA2, Implicated in HypertensionJ. Mol. Biol. doi:10.1016/j.jmb.2009.12.055. 


73. Zaitlen, Noah; Pasaniuc, Bogdan; Gur, Tom; Ziv, Elad; Halperin, Eran (2009) Leveraging Genetic Variability across Populations for the Identification of Causal Variants. The American Journal of Human Genetics, volume 86, issue 1 pp.23 - 33.


72. Levy A, Schwartz S, Ast G, (2009) Large-scale discovery of insertion hotspots and preferential integration sites of human transposed elementsNucleic Acids Research. doi:10.1093/nar/gkp1134.


71. Vanunu O, Magger O, Ruppin E, Shlomi T, Sharan R (2010) Associating Genes and Protein Complexes with Disease via Network Propagation. PLoS Comput Biol Vol 6 (1), e1000641. 


70. Shlomi,S., Cabili, N.M. and Ruppin, R. (2009) Predicting metabolic biomarkers of human inborn errors of metabolism (2009) Mol Syst Biol. 5: 263. 


69. Hüffner, F., Komusiewicz, C.,  Moser, H., and Niedermeier, R. (2008) Fixed-Parameter Algorithms for Cluster Vertex Deletion. Theory of Computing Systems. 1432-4350. 


68. Gal-Mark N, Schwartz S, Ram O, Eyras E, Ast G (2009) The Pivotal Roles of TIA Proteins in 59 Splice-Site Selection of Alu Exons and Across Evolution. PLoS Genet 5(11): e1000717. doi:10.1371/journal.pgen.1000717.


67. Waldman, Y., Tuller, T., Sharan, R., Ruppin, E. (2009). TP53 Cancerous Mutations Exhibit Selection for Translation Efficiency. Cancer Research 69, 8807-8813. 


66. Tuller,T., Rubinstein, U., BAR, D., Gurevitch,M., Ruppin,E. and Kupiec, M. (2009) Higher-Order Genomic Organization of Cellular Functions in YeastJournal of Computational Biology, Vol. 16, Number 2. 


65. Tuller, T., Ruppin E., and Kupiec, M., (2009) Properties of untranslated regions of the S. cerevisiae genome. BMC Genomics, 10:391 doi:10.1186/1471-2164-10-391. 


64. Freilich, S., Goldovsky, L., Gottlieb, A., Blanc, E., Tsoka, S. and Ouzounis, C.A. (2009) Stratification of co-evolving genomic groups using ranked phylogenetic profiles. BMC Bioinformatics 2009, 10:355 doi:10.1186/1471-2105-10-355. 


63. Jin, G., Nakhleh, L., Snir, S., Tuller, T. (2009) Parsimony Score of Phylogenetic Networks: Hardness Results and a Linear-Time Heuristic. Transactions on Computational Biology and Bioinformatics, Vol 6, Issue 3, pp 495-505. 


62. Tuller T.,Kupiec M., Ruppin, E. (2009) Co-evolutionary networks of genes and cellular processes across fungal species. Genome Biology, 10:R48doi:10.1186/gb-2009-10-5-r48. 


61. Y. Halperin, C. Linhart, I. Ulitsky and R. Shamir (2009) Allegro: Analyzing expression and sequence in concert to discover regulatory programs. Nucleic Acids Research 37:5, 1566-1579. 


60. Friedrich Förster , Keren Lasker , Florian Beck, Stephan Nickell, Andrej Sali and Wolfgang Baumeister (2009) An atomic model AAA-ATPase/20S core particle sub-complex of the 26S proteasome. Biochemical and Biophysical Research Communications,Volume 388, Issue 2, Pages 228-233. 


59. Ziv-Ukelson M., Gat-Viks, I., Wexler Y. and Shamir R. (2008) A Faster Algorithm for RNA Co-folding. Algorithms in Bioinformatics,  International Workshop on Algorithms in Bioinformatics, WABI 2008: Algorithms in Bioinformatics pp 174-185. 


58. Kifer I., Nussinov R. and Wolfson, H. J. (2008) Constructing Templates for Protein Structure Prediction by Simulation of Protein Folding Pathways. Proteins. 2008 November 1; 73(2): 380–394. doi: 10.1002/prot.22073. 


57. Snir S. and Tuller T. (2009) The Net-HMM Approach: Phylogenetic Network Inference by Combining Maximum Likelihood and Hidden Markov Models. Journal of Bioinformatics and Computational Biology Vol. 7, No. 4 (2009) 625–644 


56. Gurevich, M., Tuller, T., Rubinstein, U., Or-Bach, R. and Achiron, A.(2009) Prediction of acute multiple sclerosis relapses by transcription levels of peripheral blood cells. BMC Medical Genomics 2009, 2:46 doi:10.1186/1755-8794-2-46 


55. E. Halperin, D.A. Stephan (2009) Maximizing Power in Association Studies. Nature Biotechnology. 27: 255 - 256.


54. F. Swidan, R. Shamir (2009) Assessing the Quality of Whole Genome Alignments in Bacteria.  Advances in Bioinformatics, vol. 2009, Article ID 749027, 8 pages, 2009. doi:10.1155/2009/749027. 


53. Rubinstein ND, Mayrose I, Martz E, Pupko T. (2009) Epitopia : a web-server for predicting B-cell epitopes. BMC Bioinformatics , 10, 287.


52. Osnat Atias, Benny Chor and Daniel A Chamovitz (2009) Large-scale analysis of Arabidopsis transcription reveals a basal co-regulation networkBMC Systems Biology, 3:86doi:10.1186/1752-0509-3-86.


51. Cohen-Gihon I, Sharan R. and Nussinov, R (2009) Rearrangements and the expansion of the domain content in proteins frequently increase the protein connectivity in the protein-protein interaction network. Book chapter in Computational Protein- Protein Interactions (Schreiber, G. & Nussinov, R., eds.), published by Taylor and Francis, CRC press (2009) 


50. Pasaniuc, B., Sankararaman, S., Kimmel, G. & Halperin, E. (2009) Inference oflocus-specific ancestry in closely related populations. Bioinformatics 25,i213-i221. 


49. Sankararaman, S., Obozinski, G., Jordan, M. I. & Halperin, E. (2009) Genomic privacyand limits of individual detection in a pool. Nat Genet 41, 965-967.


48. E. Halperin, D.A. Stephan (2009) SNP Imputation in Association Studies.Nature Biotechnology. 27: 349 – 351. 


47. Schwartz S., Meshorer E., Ast G. (2009) Chromatin organization marks exon-intron structure. Nature Structural and Molecular Biology, Published online: 16 August 2009,doi: 10.1038/nsmb.1659.


46. Freilich S, Goldovsky L, Ouzounis CA, Thornton JM (2008) Metabolic innovations towards the human lineage. BMC evolutionary biology Sep 2008, 8:247. 


45. Freilich S, Kreimer A, Borenstein E, Yosef N, Sharan R, Gophna U, Ruppin E (2009) Metabolic-network-driven analysis of bacterial ecological strategies. Genome biology, 10(6):R61. 


44. Burstein D, Zusman T, Degtyar E, Viner R, Segal G, et al. (2009) Genome-Scale Identification of Legionella pneumophila Effectors Using a Machine Learning Approach. PLoS Pathog 5(7): e1000508. doi:10.1371/journal.ppat. 1000508 


43. Sharon Bruckner, Falk Hüffner, Richard M. Karp, Ron Shamir, and RodedSharan (2009) Topology-free querying of protein interaction networks.In Proceedings of the 13th Annual International Conference on Research in Computational Molecular Biology (RECOMB '09). 


42. Falk Hüffner (2009) Algorithm engineering for optimal graph bipartization.Journal of Graph Algorithms and Applications, 13(2):77-98. 


41. Lasker K, Topf M, Sali A, Wolfson HJ. (2009) Inferential optimization for simultaneous fitting of multiple components into a cryoEM map of their assembly. J. Mol. Biol. 388, 180-194, 2009. 


40. Topf M, Lasker K, Webb B, Wolfson H, Chiu W, Sali A. (2008) Protein structure fitting and refinement guided by cryo-EM density. Structure 16,295-307


39. Schwartz S, Gal-Mark N, Kfir N, Oren R, Kim E, Ast G.  (2009) Alu exonization events reveal features required for precise recognition of exons by the splicing machinery. PLoS Comput Biol., e1000300. 


38. Schwartz S, Hall E, Ast G. (2009) SROOGLE: webserver for integrative, user-friendly visualization of splicing signalsNucleic Acids ResDOI: 10.1093/nar/gkp320.


37. E. Halperin, D.A. Stephan (2009) Maximizing Power in Association Studies. Nature Biotechnology. 27: 255 - 256 


36. Karni, S., Soreq, H. and Sharan, R. (2009) A Network-Based Method for Predicting Disease-Causing Genes. Journal of Computational Biology. February 2009, 16(2): 181-189. 


35. Nimrod, D.R., Mayrose. I., Pupko, T (2009) A machine-learning approach for predicting B-cell epitopes. Molecular Immunology, 46: 840-847. 


34. Tuller, T., Kupiec,M., Ruppin, E. (2008) Evolutionary Rate and Gene Expression Across Different Brain Regions. Genome Biology, 9:R142. 


33. Shlomi, T., Cabili, M.N., Herrgard. M.J., Palsson, B.O. and Ruppin, E. (2008) Network-Based Prediction of Human Tissue-Specific Metabolism. Nature Biotechnology, 26: 1003-1010. 


32. Cohen, O., Rubinstein, ND., Stern, A., Gophna, U., and Pupko, T. (2008) A likelihood framework to analyze phyletic patterns. Philos Trans R Soc Lond B Biol Sci. 363:3903-3911. 


31. Penn, O., Stern, A., Rubinstein, ND., Dutheil, J., Bacharach, E., Galtier, N., and Pupko, T (2008) Evolutionary modeling of rate shifts reveals specificity determinants in HIV-1 subtypes. PLoS Comput Biol. 4(11):e1000214.


30. Karlebach, G., Shamir, R. (2008) Modeling and Analysis of Gene Regulatory Networks. Nature Reviews Molecular Cell Biology, Vol. 9 771-780 doi:10.1038/nrm2503. 


29. Guy Nimrod, Maya Schushan, David Steinberg and Nir Ben-Tal. (2008). Detection of Functionally Important Regions in “Hypothetical Proteins” of Known Structure. Structure, 16: 1755-1763. 


28. Nelly Andrusier, Efrat Mashiach, Ruth Nussinov and Haim J. Wolfson (2008) Principles of flexible protein-protein dockingProteins, 2008 Nov 1;73(2):271-89. 


27. F.J. Mueller, D. Kostka, L. Laurent, I. Ulitsky, R. Williams, C. Lu, M.S. Rao, R. Shamir, P.H. Schwartz, N.O. Schmidt and J.F. Loring (2008) Regulatory networks define phenotypic classes of human stem cell lines. Nature 2008 Vol. 455 No. 7211 p. 401-405 (2008).


26. Rubinstein ND, Mayrose I, Halperin D, Yekutieli D, Gershoni JM, Pupko T (2008) Computational characterization of B-cell epitopes. Mol Immunol. 2008 Jul;45(12):3477-89. Epub 2007 Nov 26. 


25. Mayrose, I., Penn, O., Erez, E., Rubinstein, ND., Shlomi, T., Tarnovitski Freund, N., Bublil, E., Rupin, E., Sharan, R., Gershoni, JM., Martz, E., and Pupko, T. (2007) Pepitope: epitope mapping from affinity-selected peptides. Bioinformatics 23(23):3244-3246. 


24. I. Ulitsky, T. Shlomi , M. Kupiec and R. Shamir (2008) From E-MAPs to module maps: dissecting quantitative genetic interactions using physical interactions. Molecular Systems Biology, 4 (2008) doi:10.1038/msb.2008.42.


23. I. Ulitsky, R.M. Karp and R. Shamir (2008) Detecting disease-specific disregulated pathways via analysis of clinical expression profiles. Proceedings of RECOMB 2008 Lecture Notes in Computer Science Vol. 4955. 


22. L.C. Laurent, J. Chen, I. Ulitsky, F.J Mueller, C. Lu, R.Shamir, J.B. Fan and J.F. Loring (2008) Comprehensive MicroRNA Profiling Reveals a Unique Human Embryonic Stem Cell Signature Dominated by a Single Seed Sequences. Stem Cells26(6):1506-16. doi: 10.1634/stemcells.2007-1081. Epub 2008 Apr 10.


21. I. Ulitsky, I. Gat-Viks and R. Shamir (2008)  MetaReg: A Platform for Modeling, Analysis and Visualization of Biological Systems Using Large-Scale Experimental Data. Genome Biology, 9, no. R1. 


20. R. Elkon, R. Vesterman, N. Amit, I. Ulitsky, M. Weisz, N. Orlev, G. Sternberg, R. Blekhman, , I. Zohar, G. Mass, J. Assa, Y. Shiloh and R. Shamir (2008) SPIKE: A Database, Visualization and Analysis Tool of Cellular Signaling Pathways. BMC Bioinformatics (2008) 9:110. 


19. Efrat Mashiach, Dina Schneidman-Duhovny, Nelly Andrusier, Ruth Nussinov and Haim J. Wolfson (2008) FireDock: a web server for fast interaction refinement in molecular docking. Nucleic Acids Res, 36:229-232, 2008.


18. Bunimovich-Mendrazitsky S., Byrne H.M., Stone L. (2008) Mathematical Model of Pulsed Immunotherapy for Superficial Bladder Cancer. Bulletin of Mathematical Biology, 70:2055-2076. 


17. Ram Oren, Schwartz Schraga and Gil Ast (2008)  Multifactorial interplay controls the splicing profile of Alu-derived exons. Molecular and Cellular Biology, 2008 May;28(10):3513-25.  


16. Gal-Mark Nurit, Schraga Schwartz, Gil Ast (2008) Alternative splicing of Alu exons – Two arms are better than one. Nucleic Acides Res, 36(6): 2012–2023, Published online 2008 Feb 14. doi: 10.1093/nar/gkn024. 


15. Schwartz Schraga, João Silva, David Burstein, Tal Pupko , Eduardo Eyras , Gil Ast  (2008) Large-scale comparative analysis of splicing signals and their corresponding splicing factors in eukaryotes. Genome Research , 18:88-103. 


14. Guohua Jin, Luay Nakhleh, Sagi Snir, Tamir Tuller (2007) A New Linear-Time Heuristic Algorithm for Computing the Parsimony Score of Phylogenetic Networks: Theoretical Bounds and Empirical Performance. ISBRA 2007: 61-72.


13. Eddo Kim, Alon Magen, Gil Ast . (2007) Different levels of alternative splicing among eukaryotes. Nucleic Acids Res. 35:125-31. 


12. Tuller, T., Kupiec, M., and Ruppin, E. (2007) Determinants of Protein Abundance and Translation Efficiency in S. Cerevisiae. PLoS Computational Biology 3 (12 ):e248. 


11. Birin, H., Gal-Or, Z., Elias, I., Tuller, T. (2007) Inferring Models of Rearrangements, Recombinations, and Horizontal Transfers by the Minimum Evolution CriterionIn: Giancarlo R., Hannenhalli S. (eds) Algorithms in Bioinformatics. WABI 2007. Lecture Notes in Computer Science, vol 4645. Springer, Berlin, Heidelberg.


10. Ulitsky, I. and Shamir, R. (2007) Pathway redundancy and protein essentiality revealed in the Saccharomyces cerevisiae interaction networks. Molecular systems biology, 3, 104. 


9. Ulitsky, I. and Shamir, R. (2007) Identification of functional modules using network topology and high-throughput data. BMC systems biology, 1, 8. 


8. Tuller, T., Chor, B. and Nelson, N. (2007) Forbidden penta-peptides. Protein Sci, 16, 2251-9. 


7. Stern, A., Privman, E., Rasis, M., Lavi, S. and Pupko, T. (2007) Evolution of the metazoan protein phosphatase 2C superfamily. Journal of molecular evolution, 64, 61-70. 


6. Sharan, R., Ulitsky, I. and Shamir, R. (2007) Network-based prediction of protein function. Molecular systems biology, 3, 88. 


5. Ninio, M., Privman, E., Pupko, T. and Friedman, N. (2007) Phylogeny reconstruction: increasing the accuracy of pairwise distance estimation using Bayesian inference of evolutionary rates. Bioinformatics (Oxford, England), 23, e136-41. 


4. Mayrose, I., Shlomi, T., Rubinstein, N.D., Gershoni, J.M., Ruppin, E., Sharan, R. and Pupko, T. (2007) Epitope mapping using combinatorial phage-display libraries: a graph-based algorithm. Nucleic acids research, 35, 69-78. 


3. Cohen-Gihon, I., Nussinov, R. and Sharan, R. (2007) Comprehensive analysis of co-occurring domain sets in yeast proteins. BMC genomics, 8, 161. 


2. Bublil, E.M., Freund, N.T., Mayrose, I., Penn, O., Roitburd-Berman, A., Rubinstein, N.D., Pupko, T. and Gershoni, J.M. (2007) Stepwise prediction of conformational discontinuous B-cell epitopes using the Mapitope algorithm. Proteins, 68, 294-304. 


1. Goren, A., Ram, O., Amit, M., Keren, H., Lev-Maor, G., Vig, I., Pupko, T. and Ast, G. (2006) Comparative analysis identifies exonic splicing regulatory sequences--The complex definition of enhancers and silencers. Molecular cell, 22, 769-81. 


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