Hi, my name is Tommi Mäklin. I’m currently
working towards a PhD in the trinity of Bayesian statistics,
bioinformatics, and machine learning at the Helsinki
Institute for Information Technology of the University of
Helsinki, Finland, where I develop probabilistic models for
bacterial (meta)genomics. My research aims to study
microbial community dynamics and host-pathogen interactions
from bacterial cultures containing multiple strains or
species through the use of high-throughput DNA sequencing
data. Our focus is on common human pathogens, their
antibiotic resistant variants, and the evolution of the
beneficial human microbiome in the presence and absence of
antibiotic treatment. We mostly work with sequencing data
from developing countries and western hospitals.
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 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 up-to-date CV is available here.
High-resolution sweep metagenomics using ultrafast read
mapping and inference
T. Mäklin, T. Kallonen, S. David, B. Pascoe, G. Méric, D. M. Aanensen, E. J. Feil, S. K. Sheppard, J. Corander, and A. Honkela.
Preprint, bioRxiv (2018).
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