Jan Komorowski

Professor at Department of Cell and Molecular Biology; Computational Biology and Bioinformatics

Telephone:: +46 18 471 66 92
Mobile phone:: +46 70 425 07 75
E-mail:: Jan.Komorowski@icm.uu.se
Visiting address:: Husargatan 3
752 37 Uppsala
Postal address:: Box 596
751 24 UPPSALA

Download contact information for Jan Komorowski at Department of Cell and Molecular Biology; Computational Biology and Bioinformatics

ORCID:: 0000-0002-0766-8789

Short presentation

Dr. Jan Komorowski is an international leader in the area of Artificial Intelligence for Life Sciences. His research focuses on modelling biological systems from big genomic data with machine learning and statistical methods. At the center of his work are models of complex regulatory mechanisms as they change in response to genetic and environmental factors. Dr. Komorowski has spearheaded applications of rule-based modelling using rough sets and introduced the concept of rule networks.

Keywords

Biography

Dr. Komorowski received an MSc in Computer Science at the Department of Computer Science at University of Warsaw, Poland, and a PhD in Computer Science at Linköping University, Sweden. Dr. Komorowski was Assistant Professor at Harvard University, Adjunct Professor at MIT, and Full Professor of Computer Science at the Norwegian Institute of Technology in Trondheim, Norway. He was Visiting Professor at Åbo Akademi University in Turku, Finland.

In 2002 he was appointed Full Professor and Chair of Bioinformatics at Uppsala University and Director of the Linnaeus Centre for Bioinformatics that he lead until 2010. In 2018 he received the honorary title of Kurt Mothes Visiting Professorship of Martin Luther University in Halle, Germany. Dr. Komorowski is also a Visiting Professor at the Institute of Computer Science, Polish Academy of Sciences, Warszawa. Currently, Dr. Komorowski is Senior Professor of Bioinformatics and Fellow at the Swedish Collegium for Advanced Study. He also holds an affiliate faculty position Division of Infectious Disease & Translational Medicine Division, University of Washington, Seattle.

Dr. Komorowski has published extensively, among others, in Nature Genetics, Genome Research, Nature, Nucleic Acid Research, Nature Communications and Bioinformatics. He is a well-cited bioinformatician with 7,405 citations at Web of Science and 14,592 at Google Scholar. As of August 2019 his h-indices were: 29 - Web of Science, and 43 - Google Scholar. 20 PhD’s graduated under his advisorship. He contributed to the ENCODE project and is currently a member of the PanCancer consortium. Dr. Komorowski currently holds a prestigious NIH award to develop computational models of immune protection by SIV/HIV vaccines, is a Senior Program Committee Member of the IJCAI 2019 and chaired the 2019 Science for Life Laboratory Summit AI for Life Sciences.

Publications

Recent publications

All publications

Articles in journal

Articles, review/survey

Rough sets in bioinformatics

Hvidsten, Torgeir R.; Komorowski, Jan

Part of Transactions on Rough Sets VII: Lecture Notes in Computer Science 4400, p. 225-243, 2007

Chapters in book

Discovering Networks of Interdependent Features in High-Dimensional Problems

Dramiński, Michał; Da̧browski, Michał J.; Diamanti, Klev; Koronacki, Jacek et al.

Part of Big Data Analysis, p. 285-304, Springer, 2016
- DOI for Discovering Networks of Interdependent Features in High-Dimensional Problems
Learning Rule-Based Models - The Rough Set Approach

Komorowski, Jan

Part of Comprehensive Biomedical Physics, p. 19-39, Elsevier, 2014
- DOI for Learning Rule-Based Models - The Rough Set Approach
Monte Carlo feature selection and interdependency discovery in supervised classification

Dramiński, Michał; Kierczak, Marcin; Koronacki, Jacek; Komorowski, Jan

Part of Advances in Machine Learning, Springer, 2010
- Download full text (pdf) of Monte Carlo feature selection and interdependency discovery in supervised classification

Conference papers

Visualization of Rules in Rule-Based Classifiers

Bornelöv, Susanne; Enroth, Stefan; Komorowski, Jan

Part of INTELLIGENT DECISION TECHNOLOGIES (IDT'2012), VOL 1, p. 329-338, 2012
- DOI for Visualization of Rules in Rule-Based Classifiers
Construction of Rough Set-Based Classifiers for Predicting HIV Resistance to Nucleoside Reverse Transcriptase Inhibitors

Kierczak, Marcin; Rudnicki, Witold; Komorowski, Jan

Part of GRANULAR COMPUTING, p. 249-258, 2008
- DOI for Construction of Rough Set-Based Classifiers for Predicting HIV Resistance to Nucleoside Reverse Transcriptase Inhibitors
RoSy: A Rough Knowledge Base System

Andersson, Robin; Vitoria, Aida; Maluszynski, Jan; Komorowski, Jan

Part of Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, p. 48-58, 2005
- DOI for RoSy: A Rough Knowledge Base System
Altered gene expression in the olfactory bulb following exposure to 2,6-dichlorophenyl methylsulfone

Bergström, Ulrika; Olsson, Jan A; Hvidsten, Torgeir R; Komorowski, Jan et al.

Part of Toxicology Letters 158 Supp 1., p. 61, 2005

Datasets

Manuscripts (preprints)

Integration of whole-body PET/MRI with non-targeted metabolomics provides new insights into insulin sensitivity of various tissues

Diamanti, Klev; Visvanathar, Robin; Pereira, Maria J; Cavalli, Marco et al.
||-ROSETTA

Baltzer, Nicholas; Komorowski, Jan
VisuNet: an interactive tool for rule network visualization of rule-based learning models

Smolinska, Karolina; Garbulowski, Mateusz; Diamanti, Klev; Davoy, Xavier et al.

Part of SUPPLEMENTARY MATERIAL: VisuNet: an interactive tool for rule network visualization of rule-based learning models
funMotifs: Tissue-specific transcription factor motifs

Smolinska, Karolina; Umer, Husen M.; Khaliq, Zeeshan; Marzouka, Nour-al-dain et al.

Part of SUPPLEMENTARY MATERIAL: funMotifs: Tissue-specific transcription factor motifs
Risk Stratification in Cervical Cancer Screening – Validation and Generalization of a Data-driven Screening Recall Model

Baltzer, Nicholas; Komorowski, Jan; Sundström, Karin; Nygård, Jan et al.
ChIP-seq in steatohepatitis and normal liver tissue identifies candidate disease mechanisms related to progression to cancer

Bysani, Madhusudhan Reddy; Wallerman, Ola; Bornelöv, Susanne; Zatloukal, Kurt et al.