mACPpred: A Support Vector Machine-Based Meta-Predictor for Identification of Anticancer Peptides

mACPpred: A Support Vector Machine-Based Meta-Predictor for Identification of Anticancer Peptides

Anticancer peptides (ACPs) are promising therapeutic agents for targeting and killing cancer cells. The accurate prediction of ACPs from given peptide sequences remains as an open problem in the field of immunoinformatics. Recently, machine learning algorithms have emerged as a promising tool for he...

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Bibliographic Details
Main Authors: Vinothini Boopathi, Sathiyamoorthy Subramaniyam, Adeel Malik, Gwang Lee, Balachandran Manavalan, Deok-Chun Yang
Format: Article
Language:English
Published: MDPI AG 2019-04-01
Series:International Journal of Molecular Sciences
Subjects:
anticancer peptides
support vector machine
feature selection
optimal features
sequential forward search
Online Access:https://www.mdpi.com/1422-0067/20/8/1964

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