Journal article
Bastion6: A bioinformatics approach for accurate prediction of type VI secreted effectors
J Jiaweiwang, B Yang, A Leier, TT Marquez-Lago, M Hayashida, A Rocker, Y Zhang, T Akutsu, KC Chou, RA Strugnell, J Song, T Lithgow
Bioinformatics | OXFORD UNIV PRESS | Published : 2018
Abstract
Motivation: 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. Results: We extracted a wide range of features from T6SE protein sequences and comprehensively analyzed the prediction performance of these features throug..
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Grants
Awarded by School of Medicine, University of Alabama at Birmingham
Funding Acknowledgements
This work was supported by grants from the National Health and Medical Research Council of Australia (NHMRC) (1092262), the Australian Research Council (ARC), the National Institute of Allergy and Infectious Diseases of the National Institutes of Health (R01 AI111965) and the Natural Science Foundation of Guangxi Under No. 2016GXNSFCA380005. AL and TML were supported by informatics startup packages through the UAB School of Medicine. T.L. is an ARC Australian Laureate Fellow (FL130100038).