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 Michael Hallett

Title of talk:
Tools for Exploring Biological Networks

Date:
December 15, 2004

Affiliation:
McGill Centre for Bioinformatics

Abstract:
This talk will present a probabilistic approach to investigating three problems related to biological networks:
the de novo inference of networks, the purification of existing networks and the use of these networks as predictors. Probabilistic models of biological networks are an important element of so-called “integrative bioinformatics” and allow us to test hypotheses by combining many heterogeneous types of information within a coherent statistical framework. A nice property of this framework is that we can assign a “belief” to each element of the putative network. We will show how our model is used in three different domains: the ER Associated Degradation pathway (ERAD), the TGF-beta pathway, and glucocorticoid receptor (GR) regulation.

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Student Speaker:
Alison Meynert, Bioinformatics Training Program for Health Research

Title of talk:
Common Evidence Network: Investigating Medline co-citations of candidate disease genes

Presentation:
Download PDF PPT

 

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