Exhaustive search of maximal biclusters in gene expression data

Yoshifumi Okada, Wataru Fujibuchi, Paul Horton

研究成果: Conference contribution

摘要

Recently, several methods have been suggested to discover biclusters from gene expression data matrices, where a bicluster is defined as a subset of genes that exhibit a highly correlated expression pattern over a subset of conditions. Most of them produce sub-optimal biclusters with greedy or stochastic approach. In contrast, we propose a new biclustering method, BiModule, that exhaustively searches biclusters in a realistic time based on a closed itemset mining algorithm. Comparative experiments to salient biclustering methods are performed to test the validity of biclusters extracted by BiModule using synthetic data and real expression data. We show that BiModule provides high performance compared to the other methods in extracting artificially-embedded modules as well as modules strongly related to GO annotations and protein-protein interactions.

原文English
主出版物標題IMECS 2007 - International MultiConference of Engineers and Computer Scientists 2007
頁面307-312
頁數6
出版狀態Published - 2007 十二月 1
事件International MultiConference of Engineers and Computer Scientists 2007, IMECS 2007 - Kowloon, Hong Kong
持續時間: 2007 三月 212007 三月 23

出版系列

名字Lecture Notes in Engineering and Computer Science
ISSN(列印)2078-0958

Other

OtherInternational MultiConference of Engineers and Computer Scientists 2007, IMECS 2007
國家Hong Kong
城市Kowloon
期間07-03-2107-03-23

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)

指紋 深入研究「Exhaustive search of maximal biclusters in gene expression data」主題。共同形成了獨特的指紋。

引用此