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Analysing Tumour Heterogeneity with Advanced Statistical Models

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thesis
posted on 2018-07-09, 00:07 authored by MOHAMMAD SHAMSUR RAHMAN
Tumour heterogeneity is a phenomena, which describes the characteristics of cancer cells. Drug responsiveness and therapeutics of cancer depend on the accurate detection of tumour heterogeneity. Recent research has considered inferring tumour heterogeneity using computational models. In this thesis, we develop computational methods to infer tumour heterogeneity. The thesis makes several major research contributions: it infers the allelic composition of mutations and clonal frequencies, and discovers the known and unknown interactions between genes of single and different disease subtypes. Hence, these major contributions to computational tumour heterogeneity research give the more precise prediction of tumour heterogeneity.

History

Campus location

Australia

Principal supervisor

Gholamreza Haffari

Additional supervisor 1

Ann E. Nicholson

Year of Award

2018

Department, School or Centre

Information Technology (Monash University Clayton)

Course

Doctor of Philosophy

Degree Type

DOCTORATE

Faculty

Faculty of Information Technology