a bioinformatics approach for accurate prediction of type VI secreted effectors
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.
We extracted a wide range of features from T6SE protein sequences and comprehensively analyzed the prediction performance of these features through unsupervised and supervised learning. By integrating these features, we subsequently developed a two-layer SVM-based ensemble model with fine-grain optimized parameters, to identify potential T6SEs.
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- Wang J et al. Bastion6: a bioinformatics approach for accurate prediction of type VI secreted effectors. Bioinformatics 2018;34(15):2546-2555. DOI: 10.1093/bioinformatics/bty155.
Lithgow Group
Infection and Immunity Program
Biomedicine Discovery Institute
Faculty of Medicine, Nursing and Health Sciences
Monash University
Melbourne, VIC 3800, Australia
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