Research progress in protein posttranslational modification site prediction. (20th December 2018)

• Record Type: Journal Article
• Authors: He, Wenying; Wei, Leyi; Zou, Quan
• Is Part Of: Briefings in functional genomics. Volume 18:Number 4(2019)
• Page Start: 220
• Page End: 229
• Publication Date: 2018-12-20
• Subjects: posttranslational modification -- machine learning -- ubiquitination -- glycosylation; Genomics -- Methodology -- Periodicals; Genomics -- Technological innovations -- Periodicals; 572.86072
• DOI: 10.1093/bfgp/ely039
• Languages: English
• ISSNs: 2041-2649

Abstract

Abstract: Posttranslational modifications (PTMs) play an important role in regulating protein folding, activity and function and are involved in almost all cellular processes. Identification of PTMs of proteins is the basis for elucidating the mechanisms of cell biology and disease treatments. Compared with the laboriousness of equivalent experimental work, PTM prediction using various machine-learning methods can provide accurate, simple and rapid research solutions and generate valuable information for further laboratory studies. In this review, we manually curate most of the bioinformatics tools published since 2008. We also summarize the approaches for predicting ubiquitination sites and glycosylation sites. Moreover, we discuss the challenges of current PTM bioinformatics tools and look forward to future research possibilities.