Bioinformatics and Big Data
Professor Inge Jonassen and part of his team from the CBU (Computational Bioinformatics Unit, Department of Informatics, UiB) are working on the development and application of bioinformatics methods for analysing data descending from high-throughput measurement technologies applied to cancer samples.
The Jonassen group works on development and application of bioinformatics methods contributing to the understanding of tumors and their microenvironments, aiming to aid in selecting appropriate treatments and prediction of outcome. They are currently working on a systems medicine approach utilizing machine learning approaches targeting leukemia and development of methods to exploit the Hyperion technology to the study of tumor microenvironment interactions in solid cancers.
Jonassen leads the project AML_PM funded by ERAPerMed, including Bjørn Tore Gjertsen as a partner from CCBIO in addition to groups from Germany, the Netherlands and Canada. A postdoc in Jonassen’s group is working on developing and applying methods for analysis of various omics and single cell data generated by the partners. In this project, the group applies systems biology modeling and machine learning approaches aimed at predicting outcome and aid selection of treatment for individual patients, using a set of different experimental model systems and piloting clinical trials. For example, in a collaborative project with the Gjertsen group, results are promising, identifying single cell markers correlated with leukemia patients’ treatment response and survival.
Another postdoc associated with CCBIO is working on development and use of methods to exploit the Hyperion imaging technology to the study of tumor microenvironment interactions. Pipelines including identification and annotation of individual cells have been established and current work includes analyzing a data set generated in the Akslen group encompassing a large cohort of breast tumors with associated outcome data. Jonassen expects a number of publications to result from the work in the coming year.
Relevant to Jonassen’s work in CCBIO, he published (in BMC Bioinformatics) in 2020 a flexible and versatile workflow for RNAseq data analysis (in BMC Genomics), a comprehensive study comparing alternative approaches for characterizing DNA copy number variants, and (in Acta Neuropathologica Communications) a study showing that expression signatures seen in Parkinson are mainly driven by cell type composition. The latter work has relevance to analysis of leukemia and solid tumor data analysis where the group is now using single cell data to better dissect changes in gene expression and relations to cell types and tumor microenvironments. Jonassen contributed to a study led by the Gjertsen group showing that response to chemotherapy can be measured shortly after treatment using CYTOF, a study published in Nature Communications (early 2023).
The group will continue developing methods to utilize single-cell and high-resolution spatial data towards precision medicine. Jonassen is also increasing his engagement towards artificial intelligence and will explore ways of combining AI approaches to analyze tumor microenvironments using multi-modal information including imaging data.