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Thesis

Novel machine learning methods for cancer sequencing analysis

Abstract:

Heterogeneity is arguably one of the most important hallmarks of cancer which contributes to its drug resistance property. Cancer heterogeneity is the consequence of an evolutionary process during its development. Understanding cancer evolution will thus benefit the drug development field as well as clinical treatment of cancer.

In this thesis, I developed three novel approaches based on machine learning for the analysis of \correction{cancer evolution} using genomics data.

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Division:
MSD
Department:
NDM
Role:
Author

Contributors

Role:
Supervisor
Role:
Supervisor
Role:
Supervisor
Role:
Supervisor
More from this funder
Name:
Cancer Research UK Oxford Center
Funding agency for:
Feng, Y
Grant:
BBR00110
BBR00110
Programme:
Non-Clinical Trai. Award Oct16
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford

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