Journal
JOURNAL OF APPLIED CRYSTALLOGRAPHY
Volume 44, Issue -, Pages 424-428Publisher
INT UNION CRYSTALLOGRAPHY
DOI: 10.1107/S0021889811004481
Keywords
protein structure analysis; bioinformatics; computer programs; PyCogent
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Funding
- University of Virginia
- Jeffress Memorial Trust [J-971]
- NIH's NIGMS [U54 GM074946-01]
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To facilitate flexible and efficient structural bioinformatics analyses, new functionality for three-dimensional structure processing and analysis has been introduced into PyCogent - a popular feature-rich framework for sequence-based bioinformatics, but one which has lacked equally powerful tools for handling stuctural/coordinate-based data. Extensible Python modules have been developed, which provide object-oriented abstractions (based on a hierarchical representation of macromolecules), efficient data structures (e.g. kD-trees), fast implementations of common algorithms (e.g. surface-area calculations), read/write support for Protein Data Bank-related file formats and wrappers for external command-line applications (e.g. Stride). Integration of this code into PyCogent is symbiotic, allowing sequence-based work to benefit from structure-derived data and, reciprocally, enabling structural studies to leverage PyCogent's versatile tools for phylogenetic and evolutionary analyses.
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