抗菌肽
支持向量机
抗真菌
人气
序列(生物学)
计算机科学
抗菌剂
随机森林
计算生物学
人工智能
机器学习
生物
微生物学
生物化学
心理学
社会心理学
作者
Shaini Joseph,Shreyas Karnik,Pravin Nilawe,Valadi K. Jayaraman,Susan Idicula‐Thomas
摘要
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/.
科研通智能强力驱动
Strongly Powered by AbleSci AI