Multi-species integrative biclustering

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 insigh...

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Detalles Bibliográficos
Autores principales: Waltman, Peter, Kacmarczyk, Thadeous, Bate, Ashley R, Kearns, Daniel B, Reiss, David J, Eichenberger, Patrick, Bonneau, Richard
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Method
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2965388/
https://www.ncbi.nlm.nih.gov/pubmed/20920250
http://dx.doi.org/10.1186/gb-2010-11-9-r96
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author Waltman, Peter
Kacmarczyk, Thadeous
Bate, Ashley R
Kearns, Daniel B
Reiss, David J
Eichenberger, Patrick
Bonneau, Richard
author_facet Waltman, Peter
Kacmarczyk, Thadeous
Bate, Ashley R
Kearns, Daniel B
Reiss, David J
Eichenberger, Patrick
Bonneau, Richard
author_sort Waltman, Peter
collection PubMed
description 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.
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spelling pubmed-29653882010-10-28 Multi-species integrative biclustering Waltman, Peter Kacmarczyk, Thadeous Bate, Ashley R Kearns, Daniel B Reiss, David J Eichenberger, Patrick Bonneau, Richard Genome Biol Method 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. BioMed Central 2010 2010-09-29 /pmc/articles/PMC2965388/ /pubmed/20920250 http://dx.doi.org/10.1186/gb-2010-11-9-r96 Text en Copyright ©2010 Waltman et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Method
Waltman, Peter
Kacmarczyk, Thadeous
Bate, Ashley R
Kearns, Daniel B
Reiss, David J
Eichenberger, Patrick
Bonneau, Richard
Multi-species integrative biclustering
title Multi-species integrative biclustering
title_full Multi-species integrative biclustering
title_fullStr Multi-species integrative biclustering
title_full_unstemmed Multi-species integrative biclustering
title_short Multi-species integrative biclustering
title_sort multi-species integrative biclustering
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2965388/
https://www.ncbi.nlm.nih.gov/pubmed/20920250
http://dx.doi.org/10.1186/gb-2010-11-9-r96
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