Computational Biology and Machine Learning in Biomedicine
We are located at SciLifeLab, Sweden’s main centre for high-throughput biology, and work on computational problems in molecular biology, primarily related to evolution and genomics.
Our interests are probabilistic modelling of evolution, in particular evolution of genes and genomes, but also somatic evolution in cancer. This line of research has yielded several breakthrough methods as well as software packages. We also have a more general interest in machine learning as well as an interest in biological areas such as genome assembly, RNA editing, micro RNA, and cardiovascular disease. We have several collaborators at SciLifeLab and within the Swedish biomedical research community in general. The current teaching is focused on machine learning.
- Swedish Research Council – Mathematical models, algorithms, and tools for regulatory and comparative genomics
- SFO project at SciLifeLab – Cancer Progression
- Project within the Erasmus Mundus PhD program EuroSPIN – Adaptive evolution in primate brain
- Swedish Research Council – Algorithms for Eukaryote Comparative Genomics
- Swedish Research Council - Algorithms for genome assembly
- Project within the Swedish Foundation for Strategic Research funded Center for Industrial and Applied Mathematics – Disease progression.