PyCogent: a toolkit for making sense from sequence

被引：144

作者：

Knight, Rob ^{[1
]}

Maxwell, Peter ^{[2
]}

Birmingham, Amanda ^{[1
]}

Carnes, Jason ^{[4
]}

Caporaso, J. Gregory ^{[5
]}

Easton, Brett C. ^{[2
]}

Eaton, Michael ^{[6
]}

Hamady, Micah ^{[7
]}

Lindsay, Helen ^{[2
]}

Liu, Zongzhi

Lozupone, Catherine

McDonald, Daniel ^{[7
]}

Robeson, Michael ^{[1
,8
]}

Sammut, Raymond

Smit, Sandra ^{[1
]}

Wakefield, Matthew J. ^{[2
,3
,9
]}

Widmann, Jeremy ^{[1
]}

Wikman, Shandy ^{[1
]}

Wilson, Stephanie ^{[7
]}

Ying, Hua

Huttley, Gavin A. ^{[2
]}

机构：

[1] Univ Colorado, Dept Chem & Biochem, Boulder, CO 80309 USA

[2] Australian Natl Univ, John Curtin Sch Med Res, Computat Genom Lab, Canberra, ACT 2601, Australia

[3] Thermo Fisher Sci, Lafayette, CO USA

[4] Seattle Biomed Res Inst, Seattle, WA 98109 USA

[5] Univ Colorado, Hlth Sci Ctr, Dept Biochem & Mol Genet, Aurora, CO USA

[6] Sci Applicat Int Corp, Englewood, CO USA

[7] Univ Colorado, Dept Comp Sci, Boulder, CO 80309 USA

[8] Univ Colorado, Dept Ecol & Evolut Biol, Boulder, CO 80309 USA

[9] Walter & Eliza Hall Inst Med Res, Melbourne, Vic 3050, Australia

来源：

GENOME BIOLOGY | 2007年 / 8卷 / 08期

关键词：

D O I：

10.1186/gb-2007-8-8-r171

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

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 http://sourceforge.net/projects/pycogent.

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