Abstractions, algorithms and data structures for structural bioinformatics in PyCogent.
Abstractions, algorithms and data structures for structural bioinformatics in PyCogent.
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PyCogent 中结构生物信息学的抽象、算法和数据结构。
DOI：
10.1107/s0021889811004481
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发表时间：
2011
影响因子：
6.1
通讯作者：
Mura,Cameron
中科院分区：
文献类型：
--
作者：
Cieślik,Marcin;Derewenda,ZygmuntS;Mura,Cameron
为了方便灵活和高效的结构生物信息学分析，三维结构处理和分析的新功能被引入到基于序列的生物信息学的流行的特征丰富的框架PyCogent中，但它缺乏处理基于结构/坐标的数据的同样强大的工具。开发了可扩展的Python模块，它们提供面向对象的抽象(基于大分子的分层表示)、高效的数据结构(例如KD树)、通用算法的快速实现(例如表面积计算)、对与蛋白质数据库相关的文件格式的读/写支持以及外部命令行应用程序的包装器(例如STRIDE)。将这些代码整合到PyCogent中是共生的，使基于序列的工作受益于结构派生的数据，反过来，使结构研究能够利用PyCogent的多种工具进行系统发育和进化分析。
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.