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- W2895484279 endingPage "550" @default.
- W2895484279 startingPage "540" @default.
- W2895484279 abstract "Enzymes are proteins that act as biological catalysts to speed up cellular biochemical processes. According to their main Enzyme Commission (EC) numbers, enzymes are divided into six categories: EC-1: oxidoreductase; EC-2: transferase; EC-3: hydrolase; EC-4: lyase; EC-5: isomerase and EC-6: synthetase. Different enzymes have different biological functions and acting objects. Therefore, knowing which family an enzyme belongs to can help infer its catalytic mechanism and provide information about the relevant biological function. With the large amount of protein sequences influxing into databanks in the post-genomics age, the annotation of the family for an enzyme is very important. Since the experimental methods are cost ineffective, bioinformatics tool will be a great help for accurately classifying the family of the enzymes. In this review, we summarized the application of machine learning methods in the prediction of enzyme family from different aspects. We hope that this review will provide insights and inspirations for the researches on enzyme family classification." @default.
- W2895484279 created "2018-10-12" @default.
- W2895484279 creator A5002661071 @default.
- W2895484279 creator A5025728076 @default.
- W2895484279 creator A5027349878 @default.
- W2895484279 creator A5031322720 @default.
- W2895484279 creator A5050257316 @default.
- W2895484279 creator A5062628676 @default.
- W2895484279 date "2019-03-05" @default.
- W2895484279 modified "2023-10-18" @default.
- W2895484279 title "A Survey for Predicting Enzyme Family Classes Using Machine Learning Methods" @default.
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