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Daniel Merkle

Cancer informatics

Phone: +45 6550 2322
Webpage: Merkle lab


Department and Faculty
Department of Mathematics and Computer Science

Mathematical Modelling for Microbial Community Induced Metabolic Diseases, Novo Nordisk Challenge Programme, 46mio DKK, 2022-2028
Training Alliance for Computational Systems Chemistry (TACsy), Marie Skłodowska- Curie action 2023-2027, 4.2 mio Euro, as coordinator/PI
Complex chemical reaction networks for breakthrough scalable reservoir computing – EU Pathfinder, 3.0 mio Euro, 2022-2026, co-PI
Algorithmic Cheminformatics Meets Causality Analysis – DFF, Scientific partner: Harvard Medical School, 2.7 mio DKK, 2020-2024, as PI

Research vision
In our research we develop and exploit the potential of cross-boundary approaches based on rigorous mathematical methods, in order solve significant societal challenges related to biology, chemistry, and health. We combine various mathematical areas (e.g. category theory, graph theory) with wet-lab experimentation data. Our methods are used for analysing and designing networks of reactions. The generality of the approaches and the ease of integration of external resources, allows us to attack any huge (and potentially unknown) network.

Three key publications

Andersen, J. L., R. Fagerberg, C. Flamm, Walter Fontana, J. Kolcák, C. V.F.P. Laurent, D. Merkle, and N. Nøjgaard
European Conference on Computational Biology (ECCB) and International Conference on Intelligent Systems for Molecular Biology (ISMB), 2021, Bioinformatics, Volume 37, Pages i392–i400
doi: 10.1093/bioinformatics/btab296.
Andersen, J. L., C. Flamm, D. Merkle and P. F. Stadler
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2019, 16(2):510–523
doi: 10.1109/TCBB.2017.2781724.
Andersen, J. L., C. Flamm, D. Merkle and P. F. Stadler
Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 2019, 375(2109)
doi: 10.1098/rsta.2016.0354.