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SUMMARY:Phylogenetic Transfer of Knowledge: Beyond Comparative Approaches
DTSTART:20140616T151500
DTSTAMP:20260603T075221Z
UID:78c87c81eef5ad6baf29df8046bb698b77935577144866ae6ed9d2c0
CATEGORIES:Conferences - Seminars
DESCRIPTION:Bernard MORET\, EPFL\nAdvances in biotechnology have enabled r
 esearchers to study molecular biology from the point of view of systems\, 
 from focused efforts at functional annotation to the study of pathways\, r
 egulatory networks\, protein-protein interaction networks\, etc. However\,
  direct observation of these systems has proved difficult\, time-consuming
 \, and often unreliable. Thus computational methods have been developed to
  infer such systems from high-throughput data\, such as sequences\, gene e
 xpression levels\, ChIP-Seq signals\, etc. For the most part\, these metho
 ds have not yet proved accurate and reliable enough to be used in automate
 d analysis pipelines. Most methods used to infer biological networks rely 
 on data for a single organism\; a few attempt to leverage existing knowled
 ge about some related organisms. Today\, however\, we have data about a la
 rge variety of organisms as well as good consensus about the evolutionary 
 relationships among these organisms\, so that the latter can be used to in
 tegrate the former in a well founded manner\, thereby gaining significant 
 power in the analysis. We have coined the term Phylogenetic Transfer of Kn
 owledge (PTK) for this approach to inference and analysis. A PTK analysis 
 considers a family of organisms with known evolutionary relationships and 
 "transfers" biological knowledge among the organisms in accordance with th
 ese relationships. The output of a PTK analysis thus includes both predict
 ed (or refined) target data (such as networks) for the extant organisms an
 d inferred details about their evolutionary history. While a few ad hoc in
 ference methods used a PTK approach almost a dozen years ago\, we first pr
 ovided a global perspective on such methods just six years ago. The last f
 ew years have seen a significant increase in research in this area\, as we
 ll as new applications. We review the general approach\, show the type of 
 improvement such methods afford over pairwise comparisons\, and discuss re
 maining challenges.\nThis is joint work with Dr. Xiuwei Zhang\, EBI\, Hinx
 ton\, UK.
LOCATION:BC 420 https://plan.epfl.ch/?room==BC%20420
STATUS:CONFIRMED
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