Hi, my name is Tommi Mäklin. I’m currently
working towards a PhD in computer science (computational
biology, Bayesian statistics, and bioinformatics) at the
Helsinki Institute for Information Technology of the
University of Helsinki, Finland, where I develop new
probabilistic models and apply existing methods in analysing
sequencing data from bacteria. My research is
focused on common human pathogens and their antibiotic
resistant variants. We mostly work with sequencing data from
western hospitals and developing countries.
In addition to my research work, I teach statistics and machine learning to Finnish private and public sector organisations as an independent consultant and serve as the chair of the University of Helsinki PhD students' association, and as the secretary of both the Finnish Statistical Society and the Finnish Society for Bioinformatics. I'm also one of the organisers of the annual Helsinki Data Science Day - a networking and recruiting event that engages the data science community of Finland in both universities and corporations.
My CV is available here (last updated in April 2020).
Genomic Epidemiology with Mixed Samples
T. Mäklin, T. Kallonen, J. Alanko, V. Mäkinen, J. Corander, and A. Honkela.
High-resolution sweep metagenomics using fast probabilistic inference
T. Mäklin, T. Kallonen, S. David, C.J. Boinett, B. Pascoe, G. Méric, D. M. Aanensen, E. J. Feil, S. Baker, J. Parkhill, S. K. Sheppard, J. Corander, and A. Honkela.
Wellcome Open Research (awaiting peer review) (2020).
Identifying Bacterial Strains from Sequencing Data
T. Mäklin, J. Corander, and A. Honkela.
Data Mining for Systems Biology, pp. 1-7, Humana Press, New York, NY (2018).
Accurate bacterial genome assembly from multi-strain
enrichment cultures (video available by request)
T. Mäklin, T. Kallonen, J. Corander, and A. Honkela
PROBGEN 2018, 4-7 November, Cold Spring Harbor, NY, United States