ClassAMP: A Prediction Tool for Classification of Antimicrobial Peptides

@article{Joseph2012ClassAMPAP,
  title={ClassAMP: A Prediction Tool for Classification of Antimicrobial Peptides},
  author={Shaini Joseph and Shreyas Karnik and Pravin Nilawe and Vaidyanathan K. Jayaraman and Susan Idicula-Thomas},
  journal={IEEE/ACM Transactions on Computational Biology and Bioinformatics},
  year={2012},
  volume={9},
  pages={1535-1538}
}
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… CONTINUE READING
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