title: SiBIC: a web server for generating gene set networks based on biclusters obtained by maximal frequent itemset mining.
abstract: Detecting biclusters from expression data is useful, since biclusters are coexpressed genes under only part of all given experimental conditions. We present a software called SiBIC, which from a given expression dataset, first exhaustively enumerates biclusters, which are then merged into rather independent biclusters, which finally are used to generate gene set networks, in which a gene set assigned to one node has coexpressed genes. We evaluated each step of this procedure: 1) significance of the generated biclusters biologically and statistically, 2) biological quality of merged biclusters, and 3) biological significance of gene set networks. We emphasize that gene set networks, in which nodes are not genes but gene sets, can be more compact than usual gene networks, meaning that gene set networks are more comprehensible. SiBIC is available at http://utrecht.kuicr.kyoto-u.ac.jp:8080/miami/faces/index.jsp.
authors.affiliation: Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto, Japan.
authors.forename: Kei-ichiro
authors.initials: K
authors.lastname: Takahashi
authors.affiliation: Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto, Japan ; Creative Research Institution, Hokkaido University, Sapporo, Hokkaido, Japan.
authors.forename: Ichigaku
authors.initials: I
authors.lastname: Takigawa
authors.affiliation: Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto, Japan.
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Mamitsuka
mesh_terms: D057225:Data Mining / Q000379:methods*; D053263:Gene Regulatory Networks; D020407:Internet; D012984:Software