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dc.contributor.advisorChandra, Nagasuma
dc.contributor.authorMishra, Madhulika
dc.date.accessioned2021-02-03T05:29:34Z
dc.date.available2021-02-03T05:29:34Z
dc.date.submitted2018
dc.identifier.urihttps://etd.iisc.ac.in/handle/2005/4846
dc.description.abstractIn summary, various systems biology approaches were applied to identify a potential genesignature set to monitor CLD progression which can help in the early detection of HCC. An unbiased analysis of metabolic alterations in HCC provided a list of top-ranked variations, rerouting of metabolism in cancer and identified potential drug targets for improving chemotherapy. As a novel analysis, mutational profiles in individual patients have been linked to the most perturbed pathways and indicating that multiple types of aberrations can converge into a common phenotype. Mutation profiles associated with HCC oncogenesis were identified. The analysis also lead to the generation of a genome to phenome landscape of HCCen_US
dc.language.isoen_USen_US
dc.relation.ispartofseries;G29709
dc.rightsI grant Indian Institute of Science the right to archive and to make available my thesis or dissertation in whole or in part in all forms of media, now hereafter known. I retain all proprietary rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertationen_US
dc.subjectHepatocellular carcinomaen_US
dc.subjectMutationen_US
dc.subjectCanceren_US
dc.titleTowards precision medicine to detect, characterize and treat liver cancer: Large-scale data analyses using genome-wide networksen_US
dc.typeThesisen_US
dc.degree.namePhDen_US
dc.degree.levelDoctoralen_US
dc.degree.grantorIndian Institute of Scienceen_US
dc.degree.disciplineFaculty of Scienceen_US


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