Generation and Analysis of Large-Scale Data-DrivenMycobacterium tuberculosisFunctional Networks for Drug Target Identification

[摘要] Technological developments in large-scale biological experiments, coupled with bioinformatics tools, have opened the doors to computational approaches for the global analysis of whole genomes. This has provided the opportunity to look at genes within their context in the cell. The integration of vastamounts of data generated by these technologies provides a strategy for identifying potential drug targetswithin microbial pathogens, the causative agents of infectious diseases. As proteins are druggable targets,functional interaction networks between proteins are used to identify proteins essential to the survival,growth, and virulence of these microbial pathogens. Here we have integrated functional genomics data togenerate functional interaction networks betweenMycobacterium tuberculosisproteins and carried out computational analyses to dissect the functional interaction network produced for identifying drug targetsusing network topological properties. This study has provided the opportunity to expand the range of potential drug targets and to move towards optimal target-based strategies.

[学科分类] 生物技术