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arXiv · 1407.5218

Abstractions, Algorithms and Data Structures for Structural Bioinformatics in PyCogent

Marcin Cieslik·Zygmunt Derewenda·Cameron Mura
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Abstract

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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Marcin Cieslik, Zygmunt Derewenda, Cameron Mura. 2014-07-19. Abstractions, Algorithms and Data Structures for Structural Bioinformatics in PyCogent. https://doi.org/10.1107/s0021889811004481

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