Skip to Content »

 Paul Pavlidis

Download Seminar Poster PDF

Download PresentationPDF
Download Movie FLASH

Talk Title:
The ruin of gene network analysis by multifunctionality

Thursday, November 17th, 2011, 6:00 pm

Associate Professor, Department of Psychiatry, University of British Columbia and Member of the Brain Research Centre

Paul Pavlidis

A major goal of biology is to identify the functional relationships and interactions among genes and apply this knowledge to make predictive models. In bioinformatics, it is now routine to use various types of gene network and gene function information to interpret
high-throughput experiments. Examples include “GO enrichment”, network-motivated clustering or gene function prediction methods (e.g. “guilt by association”) and candidate gene prioritization methods. I will describe how a phenomenon we call “gene multifunctionality” distorts such analyses. Genes having high multifunctionality are the source of serious biases or artifacts that can distract attention from more interesting signals, cause
misleading results in algorithm evaluations, and generally make meaningfully applying known information on gene function extremely difficult. I will argue that this problem is ignored at our peril, and suggest some possible remedies and strategies for making progress.

Please note:
Trainees are invited to meet with the VanBUG speaker for open discussion
of both science and career paths. This takes place 4:30-5:30pm in either
the Boardroom or Lunchroom on the ground floor of the BCCRC

Recommended Readings
The impact of multifunctional genes on “guilt by association” analysis


Introductory Speaker:
Rebecca Worsley Hunt, PhD candidate, Wasserman Lab at Centre for Molecular Medicine and Therapeutics (CMMT)

Genome nucleotide composition and sequence length affect over-representation predictions of transcription factor binding sites in ChIP-based experiments