Distinguished Speaker Series: Analysis of high content microscopy data generated through automated yeast genetics
Prof. Brenda Andrews, the Charles H. Best Chair of Medical Research, Director of the Donnelly Centre for Cellular and Biomolecular Research and Professor of Molecular Genetics at the University of Toronto.
Abstract:
We have developed experimental and computational pipelines which combine array‐based yeast genetics and automated microscopy for systematic and quantitative cell biological screens or phenomics. We use the Synthetic Genetic Array (SGA) method, which automates yeast genetics, to introduce fluorescent markers of key cellular compartments or cell cycle progression, along with sensitizing mutations, into yeast mutant collections. We then perform live cell imaging on the mutant arrays using HTP confocal microscopy to quantitatively assessthe abundance and localization of our fluorescent reporters, providing cell biological readouts of specific pathways and cellular structures in response to thousands of genetic perturbations. For automated image analysis, we developed a hybrid computational pipeline that combines outlier detection and classical SVM‐driven phenotype labeling, as well as a
neural network‐based approach. We have also implemented a deep convolutional neural network, called Deep‐Loc, for automated analysis of protein localization patterns in yeast. Deep‐Loc can be applied to analysis of image data from a wide variety of screens, in order to assess proteome dynamics in response to genetic and environmental perturbations.
Host:
Prof. Martin Kupiec, marti5_kupiec@yahoo.com, Life Sciences Faculty, TAU
