DeepEnz: prediction of enzyme classification by deep learning
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Date
2021-03-30
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Indonesian Journal of Electrical Engineering and Computer Science
Abstract
Previously, the classification of enzymes was carried out by traditional
heuritic methods, however, due to the rapid increase in the number of
enzymes being discovered, new methods aimed to classify them are required.
Their goal is to increase the speed of processing and to improve the accuracy
of predictions. The Purpose of this work is to develop an approach that
predicts the enzymes’ classification. This approach is based on two axes of
artificial intelligence (AI): natural language processing (NLP) and deep
learning (DL). The results obtained in the tests show the effectiveness of this
approach. The combination of these two tools give a model with a great
capacity to extract knowledge from enzyme data to predict and classify them.
The proposed model learns through intensive training by exploiting enzyme
sequences. This work highlights the contribution of this approach to improve
the precision of enzyme classification