| dc.contributor.advisor | Chandra, Nagasuma | |
| dc.contributor.author | Mishra, Madhulika | |
| dc.date.accessioned | 2021-02-03T05:29:34Z | |
| dc.date.available | 2021-02-03T05:29:34Z | |
| dc.date.submitted | 2018 | |
| dc.identifier.uri | https://etd.iisc.ac.in/handle/2005/4846 | |
| dc.description.abstract | In 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 HCC | en_US |
| dc.language.iso | en_US | en_US |
| dc.relation.ispartofseries | ;G29709 | |
| dc.rights | I 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 dissertation | en_US |
| dc.subject | Hepatocellular carcinoma | en_US |
| dc.subject | Mutation | en_US |
| dc.subject | Cancer | en_US |
| dc.title | Towards precision medicine to detect, characterize and treat liver cancer: Large-scale data analyses using genome-wide networks | en_US |
| dc.type | Thesis | en_US |
| dc.degree.name | PhD | en_US |
| dc.degree.level | Doctoral | en_US |
| dc.degree.grantor | Indian Institute of Science | en_US |
| dc.degree.discipline | Faculty of Science | en_US |
