期刊
FRONTIERS IN MOLECULAR BIOSCIENCES
卷 8, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fmolb.2021.634141
关键词
machine learning; prediction; metabolic pathway; enzymes; biochemical reaction; substrate; metabolites
资金
- National Key R&D Program of China [2019YFA0904303]
- Major Projects of Technological Innovation in Hubei Province [2019AEA170]
- Frontier Projects of Wuhan for Application Foundation [2019010701011381]
Prediction and reconstruction of metabolic pathways play crucial roles in various fields and have become active research topics in synthetic biology. Machine learning techniques are increasingly used to handle the growing data in this field, showing state-of-the-art performance. However, challenges still exist in the reconstruction of metabolic pathways.
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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