Studies on the application of Machine learning algorithms in Computational biology

Abstract

The primary motivation of the study was aimed at identifying newlineprospective drug targets commonly found in pathogenic bacteria and newlinedesign putative inhibitors against the targets The second phase of the newlinestudy was aimed at understanding the bacterial processes at a systemic newlinelevel using machine learning algorithms and graph theory newlineThe first objective was to find drug targets which could in newlinemultiple pathogens and the second objective was to identify chemical newlineligands which will have minimal side e ect to the host while targeting newlinethe pathogens A new algorithm was developed to mine all the known newlinemetabolic networks of forty eight pathogenic bacteria and compare the newlinenetwork profile of these pathogens to humans and identify a subset newlineof enzymes exclusive to pathogens The targets hence identified were newlinefurther refined with various selection criteria imposed to pick best the newlinetargets A final list of four enzymes common to multiple pathogens newlinewere identified as targets TolC SecA RmlB and RmlC The second newlineobjective was to design inhibitors against these targets newline newline