Abstract
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.
Original language | English (US) |
---|---|
Article number | R171 |
Journal | Genome Biology |
Volume | 8 |
Issue number | 8 |
DOIs | |
State | Published - Aug 21 2007 |
Externally published | Yes |
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ASJC Scopus subject areas
- Genetics
- Cell Biology
- Ecology, Evolution, Behavior and Systematics
Cite this
PyCogent : A toolkit for making sense from sequence. / Knight, Rob; Maxwell, Peter; Birmingham, Amanda; Carnes, Jason; Caporaso, James G; 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.
In: Genome Biology, Vol. 8, No. 8, R171, 21.08.2007.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - PyCogent
T2 - A toolkit for making sense from sequence
AU - Knight, Rob
AU - Maxwell, Peter
AU - Birmingham, Amanda
AU - Carnes, Jason
AU - Caporaso, James G
AU - Easton, Brett C.
AU - Eaton, Michael
AU - Hamady, Micah
AU - Lindsay, Helen
AU - Liu, Zongzhi
AU - Lozupone, Catherine
AU - McDonald, Daniel
AU - Robeson, Michael
AU - Sammut, Raymond
AU - Smit, Sandra
AU - Wakefield, Matthew J.
AU - Widmann, Jeremy
AU - Wikman, Shandy
AU - Wilson, Stephanie
AU - Ying, Hua
AU - Huttley, Gavin A.
PY - 2007/8/21
Y1 - 2007/8/21
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=34748893838&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34748893838&partnerID=8YFLogxK
U2 - 10.1186/gb-2007-8-8-r171
DO - 10.1186/gb-2007-8-8-r171
M3 - Article
C2 - 17708774
AN - SCOPUS:34748893838
VL - 8
JO - Genome Biology
JF - Genome Biology
SN - 1474-7596
IS - 8
M1 - R171
ER -