معرفی
Kristian Flikka is an Associate Professor at the Department of Informatics, University of Bergen. His research focuses on computational methods in proteomics, bioinformatics, and mass spectrometry. He has expertise in developing tools for proteomic data analysis, including clustering algorithms, spectral quality filtering, and biomarker discovery. His work bridges computational techniques with life sciences, addressing challenges in data preprocessing, error reduction, and interpretability in AI models.
Education:
- PhD in Computational Methods in High-Throughput Proteomics Research (2007)
- MSc in Methods for Analyzing 2D Electrophoretic Gel Images (2002)
Research Interests:
His research spans proteomics, computational biology, and AI applications in time series classification. Key areas include:
- Development of open-source tools for mass spectrometry data (e.g., ms_lims)
- Prediction of membrane protein structures (BOMP program)
- Pre-analytical proteomic data treatment
- Explainable AI for end-user model interpretation
Publications:
Over 15 publications since 2002, with notable contributions in BMC Bioinformatics, Proteomics, and Nucleic Acids Research. Recent work explores XAI in time series classification, reflecting expanded interests in AI interpretability.
Awards & Grants:
No specific awards listed, but his research has been supported by grants like the Norwegian Research Council (329745, 2022-2026).
Labs/Teams:
Collaborates with interdisciplinary teams at the University of Bergen, NORCE Norwegian Research Center, and international partners (e.g., Ghent University). Active in computational proteomics and AI-driven bioinformatics projects.
