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Recent Advances on Antioxidant Identification Based on Machine Learning Methods

Author(s):

Pengmian Feng* and Lijing Feng   Pages 1 - 6 ( 6 )

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’s 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 on 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.

Affiliation:

School of Basic Medical Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu 611730, School of Sciences, North China University of Science and Technology, Tangshan 063000



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