In Silico Approach for Prediction of Antifungal Peptides

In Silico Approach for Prediction of Antifungal Peptides

This paper describes in silico models developed using a wide range of peptide features for predicting antifungal peptides (AFPs). Our analyses indicate that certain types of residue (e.g., C, G, H, K, R, Y) are more abundant in AFPs. The positional residue preference analysis reveals the prominence...

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Bibliographic Details
Main Authors: Piyush Agrawal, Sherry Bhalla, Kumardeep Chaudhary, Rajesh Kumar, Meenu Sharma, Gajendra P. S. Raghava
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-02-01
Series:Frontiers in Microbiology
Subjects:
antimicrobial peptides
antifungal peptides
amino acid composition
support vector machine
motifs
Online Access:http://journal.frontiersin.org/article/10.3389/fmicb.2018.00323/full

Internet

http://journal.frontiersin.org/article/10.3389/fmicb.2018.00323/full

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