The mission of the Foundations of Computational Health (FCHealth) programme is:
- To develop theory and computational methods for complex data and systems. We focus on scaling up computation for large numbers of genomes, machine learning methods for structured big data, as well as complex network modelling and mining.
- To develop efficient and accurate next-generation analytics tools to tackle key problems in genomic analysis, computational metabolomics, and drug resistance and network pharmacology based on the theoretical advances.
- To bridge the gap to clinical practise. We collaborate with top medical research groups and hospitals to bring our tools towards practical use in health-care decision support systems.
Tero Aittokallio is an EMBL-FIMM group leader at Institute for Molecular Medicine Finland (FIMM), where his group has a track record of collaborative projects that combine mathematical modelling with genome-wide profiling and high-throughput drug screening to provide personalized treatment predictions for patients with complex diseases.
Aristides Gionis has co-authored numerous highly cited papers in data mining. He has contributed in areas such as graph mining, social-media analysis, web mining, data clustering, and privacy-preserving data mining. His work combines basic research with strong focus on applications, supported by six-year experience in industrial research.
Keijo Heljanko is an Associate Professor in distributed systems with focus on Big Data processing. His group has pioneered the use of Big Data platforms (Hadoop, Spark) for processing genomics data. He has extensive experience in SAT-based parallel NP-complete problem solving. He is the chairman of the Aalto Science-IT HPC infrastructure and a member of the advisory board for the Finnish national HPC infrastructure.
Ville Mustonen is a computational genomics faculty member at the Sanger Institute, UK. His group develops evolutionary theory and computational methods to analyse large scale genomic data. The work is done on systems of direct relevance to human health, e.g. cancer, infectious disease and evolution of drug resistance.
Veli Mäkinen, Vice-director, is a co-author of a textbook on genome-scale algorithm design and mentor of several prominent postdocs on the topic. He has contributed to some early results on compressed text indexing and has more recently focused on tailoring those techniques to genomic data.
Juho Rousu, Director of FCHealth and leader of the KEPACO research group, focuses on machine learning for structured data, especially on small molecules (drugs, metabolites). His research has resulted in several path-breaking conceptual and methodological contributions in metabolite identification, including the state-of-the-art CSI:FingerID technology, as well as drug discovery (drug-target and drug response prediction) and genomics (biomarker discovery and GWAS methods).
Jari Saramäki is a leading expert in network science and complex systems. He has co-authored highly cited papers in weighted network methods, network-based computational social science, and in temporal networks, where he is one of the best-known pioneers of the field. Recent application areas include network neuroscience and computational immunology.