Review of Machine Learning Methods for the Prediction and Reconstruction of Metabolic Pathways

Overview

Journal Front Mol Biosci

Specialty Biology

Date 2021 Jul 5

PMID 34222327

Citations 10

Authors

Hayat Ali Shah

Juan Liu

Zhihui Yang

Jing Feng

Affiliations

Soon will be listed here.

Abstract

Prediction and reconstruction of metabolic pathways play significant roles in many fields such as genetic engineering, metabolic engineering, drug discovery, and are becoming the most active research topics in synthetic biology. With the increase of related data and with the development of machine learning techniques, there have many machine leaning based methods been proposed for prediction or reconstruction of metabolic pathways. Machine learning techniques are showing state-of-the-art performance to handle the rapidly increasing volume of data in synthetic biology. To support researchers in this field, we briefly review the research progress of metabolic pathway reconstruction and prediction based on machine learning. Some challenging issues in the reconstruction of metabolic pathways are also discussed in this paper.

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