Skip to content

Information for students, faculty and staff regarding COVID-19. (Updated: 11 May 2021)


Computional Life Science Cluster (CLiC)

Research infrastructure The Computational Life science Cluster (CLiC) aims to support researchers in understanding complex chemical and biological systems via application and development of advanced data driven and computer based modelling tools and strategies. CLiC is an Umeå node and representative within NBIS (National Bioinformatics Infrastructure Sweden) and the Umeå University data analytics platform focusing at research within the field of analysis of high-level structured and unstructured data.

Today, massive amounts of data are being generated not only in genomics, but also by other modern high-throughput ‘omics’ and sensor technologies. The ability to analyze this complex data and draw valid conclusions from them has become a bottleneck for life science researchers. CliC’s aim is to overcome this bottleneck by providing researchers with modern data analytics tools within AI/deep learning, machine learning, multivariate analysis, statistics, bioinformatics and design of experiments, for analysis of genomics (as part of NBIS), but also non-gene related data, such as downstream ‘omics’ (metabolomics), spectroscopy and imaging data. 


Our mission is to support researchers in delivering high-quality results from their research. Our uniqueness arises from our expertise – we not only understand mathematics, statistics and modelling, but we have wide domain knowledge arising from active engagement in tenths of projects in the ‘omics’ area and beyond. This means that we can ‘jump in’ to the project directly from first day and support our customers in all project’s steps, starting from experimental design, quality control of generated data, basic and more in-depth analysis, through interpretation of results, their experimental validation and publishing.


We are offering different kinds of support (i.e. packaged data analytics services, expanded data analytics support for high-throughput experimental platforms and data science support for research projects), for all types of data and research questions.


Please, contact us, we are looking forward to supporting you in your projects!

Steering Comittee

Patrik Rydén
Other position, associate professor
Per Stenberg
Associate professor


Joakim Bygdell, NBIS, System Infrastructure, Department of Chemistry
Jeanette Tångrot, Genomics Core, NBIS, Short-term Bioinformatics support, Department of Molecular Biology
Alison Churcher, NBIS/WABI, Long term Bioinformatics support, Department of Molecular Biology
Nina Norgren, WABI, Long term Bioinformatics support, Department of Molecular Biology
Hans Stenlund, Biostatistics, Department of Plant Physiology (Swedish Metabolomics Centre)