PyCogent结构生物信息学的抽象、算法和数据结构
Abstractions, Algorithms and Data Structures for Structural Bioinformatics in PyCogent
摘要：
为了促进灵活和有效的结构生物信息学分析，PyCogent引入了三维结构处理和分析的新功能，PyCogent是一个流行的功能丰富的基于序列的生物信息学框架，但缺乏同样强大的工具来处理结构/坐标数据。可扩展的Python模块已经开发出来，它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），常见算法的快速实现（例如表面积计算），对蛋白质数据库相关文件格式的读/写支持和外部命令行应用程序的包装器（例如Stride）。将此代码集成到PyCogent中是共生的，允许基于序列的工作受益于结构衍生数据，并且使结构研究能够利用PyCogent的多功能工具进行系统发育和进化分析。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
