CompLifeSci Seminar: Dr. Leo Lahti: “Trends in microbiome data science” and Dr. Manu Tamminen: “Understanding antibiotic resistance using next-generation DNA sequencing”


22.2.2019 klo 14.00 - 15.00
Dr. Leo Lahti, Department of Mathematics and Statistics, University of Turku: “Trends in microbiome data science”


Dr. Manu Tamminen, Department of Biology, University of Turku: “Understanding antibiotic resistance using next-generation DNA sequencing”

Coffee at 13:45

Leo Lahti is Docent in applied mathematics and Academy Research Fellow at the Department of Mathematics and Statistics he leads the Computational biosciences group. He obtained PhD in statistical machine learning and bioinformatics in 2010 in Aalto University, followed by a six year postdoctoral period in The Netherlands and Belgium. Lahti is also a founding member of Helsinki Computational History group and Open Knowledge Finland working groups which received Ministry of Education awards on Open Science in 2016 and 2017, respectively. His current research focuses on modern data science methods and applications in human microbiome research. More info:

Key publications:

A hierarchical Ornstein-Uhlenbeck model for stochastic time series analysis. Ville Laitinen and Leo Lahti. In: Advances in Intelligent Data Analysis XVII. Springer, 2018.

Tipping elements in the human intestinal ecosystem. Leo Lahti, Jarkko Salojärvi, Anne Salonen, Marten Scheffer, and Willem M. de Vos. Nature Communications, 5:4344, 2014

Signatures of ecological processes in microbial community time series. Karoline Faust, Franziska Bauchinger, Beatrice Laroche, Sophie de Buyl, Leo Lahti, Alex D Washburne, Didier Gonze, and Stefanie Widder. Microbiome, 6(120) 2018.

Microbial communities as dynamical systems. Didier Gonze, Katharine Z Coyte, Leo Lahti, and Karoline Faust. Current Opinion in Microbiology, 44:41–49, 2018.

Alchemy & algorithms: perspectives on the philosophy and history of open science. Leo Lahti, Filipe da Silva, Markus Petteri Laine, Viivi Lähteenoja, and Mikko Tolonen. RIO Journal, 3:e13593, 2017.

Manu Tamminen is developing and applying single cell genome sequencing techniques to gain improved insights into complex bacterial communities and their role at the emergence of antibiotic resistant bacterial strains. He defended his doctoral thesis at the University of Helsinki and has since carried out his research at MIT and ETH Zürich. He is currently employed as a senior lecturer of genetics at the University of Turku.

Key publications:

Tamminen, M., Betz, A., Thali, M., Matthews, B., Suter, M. and Narwani, A. (2018) Proteome evolution under essential resource limitation. Nature Communications 9: 4650.

Krismer, J., Tamminen, M., Fontana, S., Zenobi, R. and Narwani. A. (2017) Single-cell mass spectrometry reveals the importance of genetic diversity and plasticity for phenotypic variation in nitrogen limited Chlamydomonas. ISME Journal 11: 988-998.

Brito, I. L., Yilmaz, S., Huang, K., Xu, L., Jupiter, S.D., Jenkins, A.P., Naisilisili, W. Tamminen, M., Smillie, C.S., Wortman, J.R., Birren, B.W., Xavier, R.J., Blainey, P.C., Singh, A.K., Gevers, D., Alm, E.J. (2016) Mobile genes in the human microbiome are structured from global to individual scales. Nature 535: 435-439

Spencer, S.*, Tamminen, M.*, Preheim, S., Guo, M., Briggs, A., Brito, I., Weitz, D., Pitkänen, L., Vigneault, F., Virta, M., Alm, E. (2016) Massively parallel sequencing of single cells by epicPCR links functional genes with phylogenetic markers. ISME Journal 10: 427-436. *Equal contribution.

Tamminen, M., Virta, M., Fani, R. & Fondi, M. (2012) Analysis of plasmid relationships through gene sharing networks. Molecular Biology and Evolution 29: 1225-1240


Nurmi, Miina