iRice-MS: An integrated XGBoost model for detecting multitype post-translational modification sites in rice

Abstract Post-translational modification (PTM) refers to the covalent and enzymatic modification of proteins after protein biosynthesis, which orchestrates a variety of biological processes. Detecting PTM sites in proteome scale is one of the key steps to in-depth understanding their regulation mech...

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Bibliographic Details
Published in:Briefings in bioinformatics 2022-01, Vol.23 (1)
Main Authors: Lv, Hao, Zhang, Yang, Wang, Jia-Shu, Yuan, Shi-Shi, Sun, Zi-Jie, Dao, Fu-Ying, Guan, Zheng-Xing, Lin, Hao, Deng, Ke-Jun
Format: Article
Language:English
Subjects:
Acetylation
Biological activity
Biosynthesis
Computational Biology
Models, Biological
Oryza - metabolism
Post-translation
Protein biosynthesis
Protein Processing, Post-Translational - physiology
Proteins
Proteome - metabolism
Proteomes
Servers
Translation
Ubiquitination
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Summary:Abstract Post-translational modification (PTM) refers to the covalent and enzymatic modification of proteins after protein biosynthesis, which orchestrates a variety of biological processes. Detecting PTM sites in proteome scale is one of the key steps to in-depth understanding their regulation mechanisms. In this study, we presented an integrated method based on eXtreme Gradient Boosting (XGBoost), called iRice-MS, to identify 2-hydroxyisobutyrylation, crotonylation, malonylation, ubiquitination, succinylation and acetylation in rice. For each PTM-specific model, we adopted eight feature encoding schemes, including sequence-based features, physicochemical property-based features and spatial mapping information-based features. The optimal feature set was identified from each encoding, and their respective models were established. Extensive experimental results show that iRice-MS always display excellent performance on 5-fold cross-validation and independent dataset test. In addition, our novel approach provides the superiority to other existing tools in terms of AUC value. Based on the proposed model, a web server named iRice-MS was established and is freely accessible at http://lin-group.cn/server/iRice-MS.
ISSN:1467-5463
1477-4054
DOI:10.1093/bib/bbab486