IACP: a Sequence-based Tool for Identifying Anticancer Peptides

Overview

Journal Oncotarget

Specialty Oncology

Date 2016 Mar 5

PMID 26942877

Citations 146

Authors

Wei Chen

Hui Ding

Pengmian Feng

Hao Lin

Kuo-Chen Chou

Affiliations

Soon will be listed here.

Abstract

Cancer remains a major killer worldwide. Traditional methods of cancer treatment are expensive and have some deleterious side effects on normal cells. Fortunately, the discovery of anticancer peptides (ACPs) has paved a new way for cancer treatment. With the explosive growth of peptide sequences generated in the post genomic age, it is highly desired to develop computational methods for rapidly and effectively identifying ACPs, so as to speed up their application in treating cancer. Here we report a sequence-based predictor called iACP developed by the approach of optimizing the g-gap dipeptide components. It was demonstrated by rigorous cross-validations that the new predictor remarkably outperformed the existing predictors for the same purpose in both overall accuracy and stability. For the convenience of most experimental scientists, a publicly accessible web-server for iACP has been established at http://lin.uestc.edu.cn/server/iACP, by which users can easily obtain their desired results.

Citing Articles

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