Title: Query-based biclustering of gene expression data using Probabilistic Relational Models
Authors: Zhao, Hui
Cloots, Lore
Van den Bulcke, Tim
Wu, Yan
De Smet, Riet
Storms, Valerie
Meysman, Pieter
Engelen, Kristof
Marchal, Kathleen # ×
Issue Date: Feb-2011
Publisher: BioMed Central
Series Title: BMC Bioinformatics vol:12
Article number: S37
Abstract: Background: With the availability of large scale expression compendia it is now possible to view own findings in the light of what is already available and retrieve genes with an expression profile similar to a set of genes of interest (i.e., a query or seed set) for a subset of conditions. To that end, a query-based strategy is needed that maximally exploits the coexpression behaviour of the seed genes to guide the biclustering, but that at the same time is robust against the presence of noisy genes in the seed set as seed genes are often assumed, but not guaranteed to be coexpressed in the queried compendium. Therefore, we developed ProBic, a query-based biclustering strategy based on Probabilistic Relational Models (PRMs) that exploits the use of prior distributions to extract the information contained within the seed set.
ISSN: 1471-2105
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Centre of Microbial and Plant Genetics
Vesalius Research Centre (-)
Laboratory of Translational Genetics (VIB-KU Leuven Center for Cancer Biology)
× corresponding author
# (joint) last author

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