Public Defence: Yohan Lefol

M.Sc. Yohan Lefol at Institute of Clinical Medicine will be defending the thesis “The use of temporality within transcriptomic data” for the degree of PhD (Philosophiae Doctor).

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Photo: Ole Christian Klamas

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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: Associate Professor Carsten Daub, Karolinska Institutet, Sweden
  • Second opponent: Professor Sushma Nagaraja Grellsheid, University of Bergen 
  • Third member and chair of the evaluation committee: Professor Yvonne Böttcher, University of Oslo

Chair of the Defence

Professor Lars Eide, University of Oslo

Principal Supervisor

Researcher Diana Domanska, University of Oslo

Summary

Transcriptomics is defined as the study of RNA which in turn can give us insight on the expression of genes, that is the degree of activity exerted by each gene. This activity can in turn translate to the understanding of biological elements such as immune or metabolic activity.

One common challenge in medicine is the proper understanding of disease mechanisms, in other words, the ‘how’ of diseases. Incorrect or incomplete understanding can cause difficulties in both diagnosing, treating, and preventing a disease. Part of the difficulties in understanding diseases is that they are not static, indeed much like how a patient experiences a disease, the disease’s mechanism changes from beginning to end. It is therefore important to account for the aspect of time when researching disease mechanisms.

The work presented in this thesis details the steps, and diseases studied, in the development of a bioinformatic pipeline capable of analyzing and aiding in the interpretation of transcriptomic data collected over any number of time points, effectively creating a time line using transcriptomic data.

Additional information

Contact the research support staff.

Published Sep. 14, 2023 2:23 PM - Last modified Sep. 26, 2023 1:33 PM