iGlu_AdaBoost: Identification of Lysine Glutarylation Using the AdaBoost Classifier.


Journal

Journal of proteome research
ISSN: 1535-3907
Titre abrégé: J Proteome Res
Pays: United States
ID NLM: 101128775

Informations de publication

Date de publication:
01 01 2021
Historique:
pubmed: 23 10 2020
medline: 22 6 2021
entrez: 22 10 2020
Statut: ppublish

Résumé

Lysine glutarylation is a newly reported post-translational modification (PTM) that plays significant roles in regulating metabolic and mitochondrial processes. Accurate identification of protein glutarylation is the primary task to better investigate molecular functions and various applications. Due to the common disadvantages of the time-consuming and expensive nature of traditional biological sequencing techniques as well as the explosive growth of protein data, building precise computational models to rapidly diagnose glutarylation is a popular and feasible solution. In this work, we proposed a novel AdaBoost-based predictor called iGlu_AdaBoost to distinguish glutarylation and non-glutarylation sequences. Here, the top 37 features were chosen from a total of 1768 combined features using Chi2 following incremental feature selection (IFS) to build the model, including 188D, the composition of

Identifiants

pubmed: 33090794
doi: 10.1021/acs.jproteome.0c00314
doi:

Substances chimiques

Proteins 0
Lysine K3Z4F929H6

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

191-201

Auteurs

Lijun Dou (L)

School of Automotive and Transportation Engineering, Shenzhen Polytechnic, Shenzhen 518055, China.
Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China.

Xiaoling Li (X)

Department of Oncology, Heilongjiang Province Land Reclamation Headquarters General Hospital, Harbin 150000, China.

Lichao Zhang (L)

School of Intelligent Manufacturing and Equipment, Shenzhen Institute of Information Technology, Shenzhen 518172, China.

Huaikun Xiang (H)

School of Automotive and Transportation Engineering, Shenzhen Polytechnic, Shenzhen 518055, China.

Lei Xu (L)

School of Electronic and Communication Engineering, Shenzhen Polytechnic, Shenzhen 518055, China.

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Classifications MeSH