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Protein–DNA/RNA interactions: Machine intelligence tools and approaches in the era of artificial intelligence and big data

Cui, Feifei, Zhang, Zilong, Cao, Chen, Zou, Quan, Chen, Dong, Su, Xi·2022·PROTEOMICS
DOI 10.1002/pmic.202100197
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Abstract

With the development of artificial intelligence (AI) technologies and the availability of large amounts of biological data, computational methods for proteomics have undergone a developmental process from traditional machine learning to deep learning. This review focuses on computational approaches and tools for the prediction of protein – DNA/RNA interactions using machine intelligence techniques. We provide an overview of the development progress of computational methods and summarize the advantages and shortcomings of these methods. We further compiled applications in tasks related to the protein – DNA/RNA interactions, and pointed out possible future application trends. Moreover, biological sequence‐digitizing representation strategies used in different types of computational methods are also summarized and discussed.

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Metadata

Authors
Cui, F., Zhang, Z., Cao, C., Zou, Q., Chen, D., & Su, X.
Affiliations
  • Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu China
  • Yangtze Delta Region Institute (Quzhou) University of Electronic Science and Technology of China Quzhou China
  • College of Electrical and Information Engineering Quzhou University Quzhou China
  • Foshan Maternal and Child Health Hospital Foshan Guangdong China
ORCID
Zou, Quan
Venue
PROTEOMICS
Publisher
Wiley
Published
2022-02-13
Volume
22
Issue
8
ISSN
  • 1615-9853
  • 1615-9861
DOI
10.1002/pmic.202100197
Cited by
40
References
9
Language
en
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor)

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