Abstractions, algorithms and data structures for structural bioinformatics in PyCogent

被引:2
|
作者
Cieslik, Marcin [1 ]
Derewenda, Zygmunt S. [2 ]
Mura, Cameron [1 ]
机构
[1] Univ Virginia, Dept Chem, Charlottesville, VA 22904 USA
[2] Univ Virginia, Hlth Sci Ctr, Dept Mol Physiol & Biol Phys, Charlottesville, VA 22908 USA
来源
JOURNAL OF APPLIED CRYSTALLOGRAPHY | 2011年 / 44卷
关键词
protein structure analysis; bioinformatics; computer programs; PyCogent; PROTEIN; TOOLKIT; FILE;
D O I
10.1107/S0021889811004481
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
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.
引用
收藏
页码:424 / 428
页数:5
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