The public defence will be held as a video conference over Zoom.
The defence will follow regular procedure as far as possible, hence it will be open to the public and the audience can ask ex auditorio questions when invited to do so.
Click here to participate in the public defence
Digital Trial Lecture – time and place
Adjudication committee
- First opponent: Professor Marc Friedländer, Science for Life Laboratory, Karolinska Institutet Science Park, Stockholm University, Sweden
- Second opponent: Professor Johan Jakobsson, Wallenberg Neuroscience Center, Lund Stem Cell Center, Lund University, Sweden
- Third member and chair of the evaluation committee: Professor Yvonne Böttcher, Faculty of Medicine, University of Oslo
Chair of the Defence
Associate Professor Shuo-Wang Qiao, Faculty of Medicine, University of Oslo
Principal Supervisor
Professor II Simon Rayner, Faculty of Medicine, University of Oslo
Summary
The general bioinformatic workflow for miRNA-seq analysis includes adapter trimming, optional read collapsing, mapping, counting, differential expression analysis and determination/prediction of miRNA function. However, despite the availability of automated pipelines to simply the process, the workflow is complex, from both a biological and computational perspective and the challenges associated with each of these steps are underestimated or not well understood. Consequently, there are many opportunities to introduce errors into the analysis, leading to erroneous conclusions related to both miRNA biogenesis and function. In this thesis, different concerns within bioinformatic analysis workflow in miRNA-seq studies have been investigated. Paper I investigated the problems associated with the adapter trimming step in small RNA sequencing studies, and highlight the importance of using correct adapter sequence in trimming and the value of trying to follow FAIR principles in miRNA-seq studies. Paper II systemically investigated the miRNA annotation in miRBase to better understand how miRBase has evolved over time and the consequences of the changes that have accumulated across releases. Paper III introduce a hierarchical isomiR nomenclature and implement it within a publicly available analysis pipeline, Jasmine. Paper IV present a novel approach, miRAW, for miRNA target prediction based on deep neural networks.
Additional information
Contact the research support staff.