My research mainly focuses on the use of mathematical, computational and statistical methods and models in the area of infection biology. In recent years, my research has been directed more towards translational medicine, especially in development and application of data-mining methods on large-scale biomarker data. Although that the advent of high-throughput technologies capable of producing large-scale biological data has provided an excellent opportunity for the discovery of novel biomarkers, it has simultaneously complicated the problem of mining meaningful biomarker signatures as analysis and interpretation of such complex data require sophisticated systems biology approaches.
My ongoing research aims at developing accurate and transparent diagnosis support systems for early identification of patients with bacterial sepsis, and includes the projects Data-mining for biomarker discovery, selection, and validation (2017-2021, Knowledge Foundation), Next generation sepsis diagnosis (2016-2021, EU, H2020), Development of sepsis diagnosis system (2016-2019, Knowledge Foundation), and Microbial diversity in patients suspected with sepsis (financed through several research grants). Current research collaborators include Skaraborg Hospital, Unilabs AB, TATAA Biocenter AB, Gothenburg University, bioMérieux Sweden AB, 1928Diagnostics AB, Olink Proteomics AB, QIAGEN AB, Danska Tekniska Universitetet, Copenhagen Business School, Charles University, Danube University, Deutsches Institut fur Normung, CubeDx, and Zoetis.
I gained my master degree in Molecular Computational Biology from University of Skövde in 2004, and I defended my PhD, entitled “Studies on emergence and spread of antibiotic resistant Streptococcus pneumoniae”, at the Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet in 2010. Currently, I´m a Senior Lecturer in Systems Biology, Head of Systems Biology, a member of the Infection Biology Group and the Systems Biology Research Centre at the University of Skövde.
