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Current Drug Metabolism

Editor-in-Chief

ISSN (Print): 1389-2002
ISSN (Online): 1875-5453

Review Article

Recent Advances on Antioxidant Identification Based on Machine Learning Methods

Author(s): Pengmian Feng* and Lijing Feng

Volume 21, Issue 10, 2020

Page: [804 - 809] Pages: 6

DOI: 10.2174/1389200221666200719001449

Price: $65

Abstract

Antioxidants are molecules that can prevent damages to cells caused by free radicals. Recent studies also demonstrated that antioxidants play roles in preventing diseases. However, the number of known molecules with antioxidant activity is very small. Therefore, it is necessary to identify antioxidants from various resources. In the past several years, a series of computational methods have been proposed to identify antioxidants. In this review, we briefly summarized recent advances in computationally identifying antioxidants. The challenges and future perspectives for identifying antioxidants were also discussed. We hope this review will provide insights into researches on antioxidant identification.

Keywords: Antioxidant, free radical, diseases, sequence encoding scheme, machine learning methods, molecules.

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