Mining genomic patterns in Mycobacterium tuberculosis H37Rv using a web server Tuber-Gene.

ABSTRACT: Mycobacterium tuberculosis (MTB), causative agent of tuberculosis, is one of the most dreaded diseases of the century. It has long been studied by researchers throughout the world using various wet-lab and dry-lab techniques. In this study, we focus on mining useful patterns at genomic level that can be applied for in silico functional characterization of genes from the MTB complex. The model developed on the basis of the patterns found in this study can correctly identify 99.77% of the input genes from the genome of MTB strain H37Rv. The model was tested against four other MTB strains and the homologue M. bovis to further evaluate its generalization capability. The mean prediction accuracy was 85.76%. It was also observed that the GC content remained fairly constant throughout the genome,

SUBMITTER: Rishishwar L 

PROVIDER: S-EPMC5054438 | biostudies-literature | 2011 Oct

REPOSITORIES: biostudies-literature