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Updated: Feb 23, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
Published on: January 26, 2024
POSSUM: a bioinformatics toolkit for generating numerical sequence feature descriptors based on PSSM profiles
Jiawei Wang1, Bingjiao Yang2, Jerico Revote1
1Biomedicine Discovery Institute, Monash University, VIC 3800, Australia.
Summary:
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.
Availability And Implementation:
http://possum.erc.monash.edu/ .
Contact:
trevor.lithgow@monash.edu or jiangning.song@monash.edu.
Supplementary Information:
Supplementary data are available at Bioinformatics online.

