POSSUM: a bioinformatics toolkit for generating numerical sequence feature descriptors based on PSSM profiles.

Wang, Jiawei; Yang, Bingjiao; Revote, Jerico; Leier, André; Marquez-Lago, Tatiana T; Webb, Geoffrey; Song, Jiangning; Chou, Kuo-Chen et al. · Bioinformatics · 2017

basic_science · Level V

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Abstract

Evolutionary information in the form of a Position-Specific Scoring Matrix (PSSM) is a widely used and highly informative representation of protein sequences. Accordingly, PSSM-based feature descriptors have been successfully applied to improve the performance of various predictors of protein attributes. Even though a number of algorithms have been proposed in previous studies, there is currently no universal web server or toolkit available for generating this wide variety of descriptors. Here, we present POSSUM ( Po sition- S pecific S coring matrix-based feat u re generator for m achine learning), a versatile toolkit with an online web server that can generate 21 types of PSSM-based feature descriptors, thereby addressing a crucial need for bioinformaticians and computational biologists. We envisage that this comprehensive toolkit will be widely used as a powerful tool to facilitate feature extraction, selection, and benchmarking of machine learning-based models, thereby contributing to a more effective analysis and modeling pipeline for bioinformatics research. http://possum.erc.monash.edu/ . trevor.lithgow@monash.edu or jiangning.song@monash.edu. Supplementary data are available at Bioinformatics online.

Medical subject headings