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Multi-species integrative biclustering

Peter Waltman12, Thadeous Kacmarczyk3, Ashley R Bate3, Daniel B Kearns4, David J Reiss5, Patrick Eichenberger3* and Richard Bonneau123*

Author Affiliations

1 Computer Science Department, Warren Weaver Hall (Room 305), 251 Mercer Street, New York, NY 10012, USA

2 Computational Biology Program, New York University, Warren Weaver Hall (Room 1105), 251 Mercer Street, New York, NY 10012, USA

3 Center for Genomics and Systems Biology, Department of Biology, New York University, Silver Building (Room 1009), 100 Washington Square East, New York, NY 10003, USA

4 Department of Biology, Indiana University, 1001 East 3rd Street, Jordan Hall 142, Bloomington, IN 47405, USA

5 Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA

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Genome Biology 2010, 11:R96  doi:10.1186/gb-2010-11-9-r96

Published: 29 September 2010


We describe an algorithm, multi-species cMonkey, for the simultaneous biclustering of heterogeneous multiple-species data collections and apply the algorithm to a group of bacteria containing Bacillus subtilis, Bacillus anthracis, and Listeria monocytogenes. The algorithm reveals evolutionary insights into the surprisingly high degree of conservation of regulatory modules across these three species and allows data and insights from well-studied organisms to complement the analysis of related but less well studied organisms.