ClassAMP: a prediction tool for classification of antimicrobial peptides
Related Experiment Video
Updated: May 21, 2026
Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group
Published on: August 16, 2017
Shaini Joseph1, Shreyas Karnik, Pravin Nilawe
1Biomedical Informatics Center of Indian Council of Medical Research, National Institute for Research in Reproductive Health, Parel, Mumbai, Maharashtra, India. shainimarina31@gmail.com
Abstract:
Antimicrobial peptides (AMPs) are gaining popularity as anti-infective agents. Information on sequence features that contribute to target specificity of AMPs will aid in accelerating drug discovery programs involving them. In this study, an algorithm called ClassAMP using Random Forests (RFs) and Support Vector Machines (SVMs) has been developed to predict the propensity of a protein sequence to have antibacterial, antifungal, or antiviral activity. ClassAMP is available at http://www.bicnirrh.res.in/classamp/.
