Downloadable & Online Tools
Downloadable software tools
The research projects performed by groups in the Center involve the construction of new software tools. Invention of new approaches or computational procedures are accompanied by development of software tools and testing them on the problem data. Tools that prove useful are made available to the biomedical research world as downloadable tools/databases, or as online services.
List of downloadable software tools:
|
Group |
Tool name |
Purpose |
|---|---|---|
|
Shamir/Elkon |
Gene expression and deep sequencing data analysis |
|
|
Mayrose/ Pupko |
Detection of conserved amino-acid sites |
|
|
Mayrose |
Analysis of changes in chromosome number |
|
|
E.Halperin |
Admixture mapping |
|
|
E.Halperin |
Estimating cell type composition |
|
|
Shamir |
Design of highly degenerate primers |
|
|
Gat-Viks |
Studying the physiology of immune-cell types in complex tissues |
|
|
Halperin |
EWAS analysis. |
|
|
Shamir |
Detect regulatory motifs |
|
|
Sharan |
Biological network analysis |
|
|
Shamir |
Module analysis via topology of interactions and similarity sets |
|
|
Halperin |
Construct confidence intervals for heritability estimates |
|
|
Shamir |
Integrative analysis of biological networks |
|
|
Shamir |
Extracting circular elements from deep sequencing data |
|
|
Shomron |
Differential expression of miRNAs from NGS |
|
|
Shamir |
Joint analysis of two biological networks |
|
|
Gat-Viks |
Infer the quantities of immune cell types, and uncover DNA loci |
|
|
Shamir |
3-way module Inference |
|
|
Tuller |
Ribosome flow model |
|
|
Tuller |
Calculate translation efficiency index |
|
|
Tuller |
Calculate tRNA adaptation index |
|
|
Tuller |
Translation initiation and elongation model |
|
|
Tuller |
Analyze gene expression using the genetic code
|
|
| Tuller | ChimeraUGEM | Unsupervised Gene Expression Modeling |
|
Gat-Viks |
Identify pairwise eQTL effects on gene modules |
|
|
Gat-Viks |
Construct causative model of trait–trait connections |
|
|
Gat-Viks |
Dynamic Variant Effect on Response
|
|
|
Shamir |
Analysis of large multi-omic and clinical datasets |
|
| Borenstein | MUSiCC | Normalization and correction of microbiome gene abundance profiles |
| Borenstein | FishTaco | Quantification of taxonomic drivers of functional microbiome shifts |
| Borenstein | NetSeed | Metabolic network-based prediction of biochemical environments |
| Borenstein | NetCooperate | Prediction of host-microbe and microbe-microbe cooperation |
| Borenstein | MIMOSA | Identification of drivers of microbiome metabolomic variation |
| Borenstein | CoMiDA | An algorithm for designing simple microbial communities |
| Borenstein | EMPANADA | Evidence-based, assignment of gene families to pathways in metagenomic data |
| Borenstein | MetaDecon | Metagenomic deconvolution |
| Pasmanik-Chor | HeatMapViewer | Interactive display of 2D biological data |
| Pasmanik-Chor | BioNSi | Simulation and visualization of multiple KEGG pathways |
| Pasmanik-Chor | GEView | Intuitive visualization of expression data |
