SEMINAR: REPA: A novel method to facilitate biological interpretation of high throughput expression

Pranjal Patra
M.Sc. Candidate
Supervisor: Dr. Lourdes Pena-Castillo

Regulation and Expression Pathway Analysis or REPA: A novel method to facilitate biological interpretation of high throughput expression profiling data

Department of Computer Science
Tuesday, July 29, 2014, 12:00 p.m., Room EN 2022


Abstract

In the past decade there have been great advances and emergence of new techniques in the field of gene expression profiling. As the popularity of this technique grew, the amount of data that gets generated everyday has also grown. Therefore the need for specific techniques and tools to derive useful information from this growing data is more than ever before.

In this project we built a system called Regulation and Expression Pathway Analysis or REPA to facilitate the biological interpretation of results from such high throughput gene expression profiling experiments. Transcription factors are proteins that regulate gene expression in cells. In particular, we provide researchers with gene sets that were most active in the biological phenomenon under study and their likely regulators. Users can input the gene expression profile data from their expression profiling experiments in REPA and get a list of disturbed gene sets and inferred transcription factors that possibly regulate these gene sets.

To build this system first we processed the transcription factor binding sites data from the ENCODE project to quantify the strength of regulation that each transcription factor has on each gene set. Then we build an gene expression enrichment analysis system that can analyze the gene expression
profiling data and list the most active gene sets. Finally we combine the results from the previous two steps to arrive at a more complete picture that gives users information about not only the most active gene sets like most existing system, but also tells them the likely regulators of these gene sets.

 

Contact

Department of Computer Science

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becomestudent@mun.ca