Genome and Gene Expression Data Analysis Division
 
Dr. KUZNETSOV Vladimir
Head of Division

Details
 
Research Overview
 
This research division attempts to understand transcription regulation and its relevance for phenotypic properties of cells. Complex biological phenomena such as stem cell differentiation and cancer progression are analyzed and modeled for eliciting essential gene expression patterns and signatures, differentially co-regulated gene and protein modules, essential DNA-protein, RNA-protein, DNA-RNA interactions and other bio-molecular interaction networks.
 
Research Objectives
 
In this division, gene expression profiles and massive sequence data from DNA-binding proteins and other experiments are used. The data is quantitatively analyzed to uncover transcriptional regulatory networks and cellular programs, and this represents a step into systems biology. This division's gene expression signature approaches have considerable potential for diagnostics and prognosis tasks including clinical applications.

This division deals with several aspects of quantitative analysis of genome, transcriptome and proteome complexity - including pattern recognition, massive computational data analysis, feature selection, simulation and modeling of gene expression and transcription control, global changes expression profile on the genome scale, prediction and modeling of different types of bio-molecular networks, pathways and regulatory programs in stem cells and their differentiated progeny and also in normal and cancerous cells.

 
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