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Recent Advances in Computational Methods for Identifying Anticancer Peptides

[ Vol. 20 , Issue. 5 ]

Author(s):

Pengmian Feng* and Zhenyi Wang   Pages 481 - 487 ( 7 )

Abstract:


Anticancer peptide (ACP) is a kind of small peptides that can kill cancer cells without damaging normal cells. In recent years, ACP has been pre-clinically used for cancer treatment. Therefore, accurate identification of ACPs will promote their clinical applications. In contrast to labor-intensive experimental techniques, a series of computational methods have been proposed for identifying ACPs. In this review, we briefly summarized the current progress in computational identification of ACPs. The challenges and future perspectives in developing reliable methods for identification of ACPs were also discussed. We anticipate that this review could provide novel insights into future researches on anticancer peptides.

Keywords:

Anticancer peptides, disease, cancer, drug target, machine learning methods, sequence encoding scheme.

Affiliation:

School of Public Health, North China University of Science and Technology, Tangshan, 063000, Center for Genomics and Computational Biology, School of Life Science, North China University of Science and Technology, Tangshan, 063000

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