Applications of Natural Language Processing Techniques in Protein Structure and Function Prediction

Bin Liu*, Ke Yan, Yi He Pang, Jun Zhang, Jiang Yi Shao, Yi Jun Tang, Ning Wang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Protein structure and function prediction are instrumental areas in the bioinformatics field. They are important for a number of applications in rational drug discovery, disease analysis, and many others. Protein sequences and natural languages share some similarities. Therefore, many techniques derived from natural language processing (NLP) have been applied to the protein structure and function prediction. In this chapter, we discuss sequence-based predictors of protein structure and function that utilize techniques derived from NLP field. We include methods that target protein sequence analysis, fold recognition, identification of intrinsically disordered regions/proteins, and prediction of protein-nucleic acids binding. The concepts and computational methods discussed in this chapter will be especially useful for the researchers who are working in the related field. We also aim to bring new computational NLP techniques into the protein structure and function prediction area.

Original languageEnglish
Title of host publicationMachine Learning in Bioinformatics of Protein Sequences
Subtitle of host publicationAlgorithms, Databases and Resources for Modern Protein Bioinformatics
PublisherWorld Scientific Publishing Co.
Pages57-80
Number of pages24
ISBN (Electronic)9789811258589
ISBN (Print)9789811258572
DOIs
Publication statusPublished - 1 Jan 2022

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