Systematic analysis and prediction of type IV secreted effector proteins by machine learning approaches

Abstract In the course of infecting their hosts, pathogenic bacteria secrete numerous effectors, namely, bacterial proteins that pervert host cell biology. Many Gram-negative bacteria, including context-dependent human pathogens, use a type IV secretion system (T4SS) to translocate effectors directl...

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Veröffentlicht in:	Briefings in bioinformatics 2019-05, Vol.20 (3), p.931-951
Hauptverfasser:	Wang, Jiawei, Yang, Bingjiao, An, Yi, Marquez-Lago, Tatiana, Leier, André, Wilksch, Jonathan, Hong, Qingyang, Zhang, Yang, Hayashida, Morihiro, Akutsu, Tatsuya, Webb, Geoffrey I, Strugnell, Richard A, Song, Jiangning, Lithgow, Trevor
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Bacteria Bacterial Proteins - metabolism Bacterial Secretion Systems Bayes Theorem Cytosol Effectors Ensemble learning Gene expression Gram-negative bacteria Host-pathogen interactions Learning algorithms Machine Learning Multilayer perceptrons Pathogenesis Pathogens Performance evaluation Performance prediction Proteins Secretion Support Vector Machine Support vector machines Virulence
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