The Bioinformatics Laboratory lead by Professor Jan Komorowski is involved in the development of machine learning methods and tools applicable in Life Science research. Rather than focusing on the quality of classification, we investigate the structure of models constructed with supervised techniques, i.e. we look at feature selection and transparent model generation such as, for instance, rough set models. We have developed our own tools that include Monte Carlo Feature Selection and the Rosetta system. In addition to machine learning, we use and develop statistical methods to process high throughput data.
We collaborate with several biomedical groups in Sweden, Poland and elsewhere and work with own and public data. Studies include, but are not limited to epigenetics and the role of chromatin in gene regulation, DNA-methylation, neurodegenerative diseases and cancer. We have also made contributions to modeling aspects of pathogenicity in HIV-1 virus. A selection of our publications is included [1-6].
Applicants are expected to have a PhD in bioinformatics, computational biology or systems biology with top competence in computing and statistics.
Candidates should contact directly Prof. Jan Komorowski, email@example.com
1. Hvidsten TR, Komorowski J: Rough sets in bioinformatics. In: Transactions on rough sets VII. Edited by Victor WM, Ewa O, owska, Roman S, owinski, Wojciech Z: Springer-Verlag; 2007: 225-243.
2. ENCODE-Project-Consortium: Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project. Nature 2007, 447(7146):799-816.
3. Laegreid A, Hvidsten TR, Midelfart H, Komorowski J, Sandvik AK: Predicting gene ontology biological process from temporal gene expression patterns. Genome Research 2003, 13(5):965-979.
4. Hvidsten TR, Wilczynski B, Kryshtafovych A, Tiuryn J, Komorowski J, Fidelis K: Discovering regulatory binding-site modules using rule-based learning. Genome Research 2005, 15(6):856-866.
5. Kierczak M, Draminski M, Koronacki J, Komorowski J: Computational Analysis of Molecular Interaction Networks Underlying Change of HIV-1 Resistance to Selected Reverse Transcriptase Inhibitors. Bioinform Biol Insights 2010, 4:137-146.
6. Enroth S, Bornelov S, Wadelius C, Komorowski J: Combinations of histone modifications mark exon inclusion levels. Plos One 2012, 7(1):e29911.