Bastion6: a bioinformatics approach for accurate prediction of type VI secreted effectors | Zendy

Jiawei Wang | Zendy; Bingjiao Yang | Zendy; André Leier | Zendy; Tatiana T. MarquezLago | Zendy; Morihiro Hayashida | Zendy; Andrea Rocker | Zendy; Yanju Zhang | Zendy; Tatsuya Akutsu | Zendy; KuoChen Chou | Zendy; Richard A. Strugnell | Zendy; Jiangning Song | Zendy; Trevor Lithgow | Zendy

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Bastion6: a bioinformatics approach for accurate prediction of type VI secreted effectors

Author(s) -

Jiawei Wang,

Bingjiao Yang,

André Leier,

Tatiana T. MarquezLago,

Morihiro Hayashida,

Andrea Rocker,

Yanju Zhang,

Tatsuya Akutsu,

KuoChen Chou,

Richard A. Strugnell,

Jiangning Song,

Trevor Lithgow

Publication year - 2018

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bty155

Subject(s) - effector , computational biology , computer science , support vector machine , genome , bacterial genome size , biology , protein sequencing , machine learning , function (biology) , artificial intelligence , data mining , gene , peptide sequence , genetics , microbiology and biotechnology

Many Gram-negative bacteria use type VI secretion systems (T6SS) to export effector proteins into adjacent target cells. These secreted effectors (T6SEs) play vital roles in the competitive survival in bacterial populations, as well as pathogenesis of bacteria. Although various computational analyses have been previously applied to identify effectors secreted by certain bacterial species, there is no universal method available to accurately predict T6SS effector proteins from the growing tide of bacterial genome sequence data.

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