PyCogent: a toolkit for making sense from sequence

We have implemented in Python the COmparative GENomic Toolkit, a fully integrated and thoroughly tested framework for novel probabilistic analyses of biological sequences, devising workflows, and generating publication quality graphics. PyCogent includes connectors to remote databases, built-in gene...

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Detalles Bibliográficos
Autores principales: Knight, Rob, Maxwell, Peter, Birmingham, Amanda, Carnes, Jason, Caporaso, J Gregory, Easton, Brett C, Eaton, Michael, Hamady, Micah, Lindsay, Helen, Liu, Zongzhi, Lozupone, Catherine, McDonald, Daniel, Robeson, Michael, Sammut, Raymond, Smit, Sandra, Wakefield, Matthew J, Widmann, Jeremy, Wikman, Shandy, Wilson, Stephanie, Ying, Hua, Huttley, Gavin A
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Software
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2375001/
https://www.ncbi.nlm.nih.gov/pubmed/17708774
http://dx.doi.org/10.1186/gb-2007-8-8-r171
Descripción
Sumario:We have implemented in Python the COmparative GENomic Toolkit, a fully integrated and thoroughly tested framework for novel probabilistic analyses of biological sequences, devising workflows, and generating publication quality graphics. PyCogent includes connectors to remote databases, built-in generalized probabilistic techniques for working with biological sequences, and controllers for third-party applications. The toolkit takes advantage of parallel architectures and runs on a range of hardware and operating systems, and is available under the general public license from .

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