Computational approach to predict species-specific type III secretion system (T3SS) effectors using single and multiple genomes
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- 作者：Christopher K. Hobbs ; Vanessa L. Porter ; Maxwell L. S. Stow ; Bupe A. Siame…
- 关键词：Machine learning ; Type III secretion system ; Effector prediction ; Gram ; negative bacteria
- 刊名：BMC Genomics
- 出版年：2016
- 出版时间：December 2016
- 年：2016
- 卷：17
- 期：1
- 全文大小：593KB
- 刊物主题：Life Sciences, general; Microarrays; Proteomics; Animal Genetics and Genomics; Microbial Genetics and Genomics; Plant Genetics & Genomics;
- 出版者：BioMed Central
- ISSN：1471-2164
- 卷排序：17
文摘
BackgroundMany gram-negative bacteria use type III secretion systems (T3SSs) to translocate effector proteins into host cells. T3SS effectors can give some bacteria a competitive edge over others within the same environment and can help bacteria to invade the host cells and allow them to multiply rapidly within the host. Therefore, developing efficient methods to identify effectors scattered in bacterial genomes can lead to a better understanding of host-pathogen interactions and ultimately to important medical and biotechnological applications.