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 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.
Knight
Rob
R
Department of Chemistry and Biochemistry, University of Colorado, Boulder, Colorado, USA. rob@spot.colorado.edu
Maxwell
Peter
P
Birmingham
Amanda
A
Carnes
Jason
J
Caporaso
J Gregory
JG
Easton
Brett C
BC
Eaton
Michael
M
Hamady
Micah
M
Lindsay
Helen
H
Liu
Zongzhi
Z
Lozupone
Catherine
C
McDonald
Daniel
D
Robeson
Michael
M
Sammut
Raymond
R
Smit
Sandra
S
Wakefield
Matthew J
MJ
Widmann
Jeremy
J
Wikman
Shandy
S
Wilson
Stephanie
S
Ying
Hua
H
Huttley
Gavin A
GA
D000818:Animals; D019313:BRCA1 Protein / Q000235:genetics; D030541:Databases, Genetic; D023281:Genomics / Q000379:methods*; D006801:Humans; D010802:Phylogeny; D011487:Protein Conformation; D020560:Proteobacteria / Q000145:classification / Q000235:genetics; D017421:Sequence Analysis / Q000379:methods*; D012984:Software; D014841:von Willebrand Factor / Q000737:chemistry / Q000235:genetics
D019313:BRCA1 Protein; D014841:von Willebrand Factor
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