propy: a tool to generate various modes of Chou’s PseAAC

• DOI: 10.1093/bioinformatics/btt072
• Publication Date: 2013-02-21T03:22:10Z
• Authors: Dong-Sheng Cao; Qing-Song Xu; Yi-Zeng Liang
• Keywords: Python; R package; Tripeptide; Sequence (biology); Sequence motif

Abstract Summary: Sequence-derived structural and physiochemical features have been frequently used for analysing predicting structural, functional, expression interaction profiles of proteins peptides. To facilitate extensive studies peptides, we developed a freely available, open source python package called protein in (propy) calculating the widely physicochemical peptides from amino acid sequence. It computes five feature groups composed 13 features, including composition, dipeptide tripeptide normalized Moreau–Broto autocorrelation, Moran Geary sequence-order-coupling number, quasi-sequence-order descriptors, transition distribution various properties two types pseudo composition (PseAAC) descriptors. These could be generally regarded as different Chou’s PseAAC modes. In addition, it can also easily compute previous descriptors based on user-defined properties, which are automatically available AAindex database. Availability: The package, propy, is via http://code.google.com/p/protpy/downloads/list, runs Linux MS-Windows. Contact: [e-mail] Supplementary information: data at Bioinformatics online.