Journal article

Large-scale comparative review and assessment of computational methods for anti-cancer peptide identification.

Xiao Liang, Fuyi Li, Jinxiang Chen, Junlong Li, Hao Wu, Shuqin Li, Jiangning Song, Quanzhong Liu

Brief Bioinform | Published : 2021


Anti-cancer peptides (ACPs) are known as potential therapeutics for cancer. Due to their unique ability to target cancer cells without affecting healthy cells directly, they have been extensively studied. Many peptide-based drugs are currently evaluated in the preclinical and clinical trials. Accurate identification of ACPs has received considerable attention in recent years; as such, a number of machine learning-based methods for in silico identification of ACPs have been developed. These methods promote the research on the mechanism of ACPs therapeutics against cancer to some extent. There is a vast difference in these methods in terms of their training/testing datasets, machine learning a..

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University of Melbourne Researchers


Awarded by Australian Research Council

Awarded by National Natural Science Foundation of China

Awarded by NIAID NIH HHS

Awarded by NIH HHS

Awarded by Collaborative Research Program of Institute for Chemical Research

Awarded by National Health and Medical Research Council of Australia