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Due to copyright issues, an electronic copy of the thesis must be ordered from the faculty. For the faculty to have time to process the order, the order must be received by the faculty at the latest 2 days before the public defence. Orders received later than 2 days before the defence will not be processed. After the public defence, please address any inquiries regarding the thesis to the candidate.
Trial Lecture – time and place
See Trial Lecture.
Adjudication committee
- First opponent: Senior Director Aik Choon Tan, University of Utah, USA
- Second opponent: Associate Professor Morten Beck Rye, NTNU - Norwegian University of Science and Technology
- Third member and chair of the evaluation committee: Associate Professor June Helen Myklebust, University of Oslo
Chair of the Defence
Associate Professor Lorant Farkas, University of Oslo
Principal Supervisor
Researcher Junbai Wang, University of Oslo
Summary
Genome regulation in mammals is a complex process that involves various factors at different levels. Transcription factors bind to specific DNA sequences to guide gene expression at genomic level, while DNA methylation can also influence gene expression at epigenomic level. Understanding how these biological pathways are regulated is crucial to understanding complex disease mechanisms. However, integrating genetic and epigenetic data to achieve a comprehensive understanding of regulatory mechanisms remains challenging. To address this issue, this study proposed new integrative data analysis techniques by merging genetic and epigenetic datasets using data mining or machine learning techniques. By using these methods, the thesis identified several biomarkers and potential therapeutic targets for follicular lymphoma, a type of cancer. These integrative methods can also be used to study long-distance gene regulation and other complex diseases.
Additional information
Contact the research support staff.