Our research focuses on computational analysis and understanding of complex natural and social systems. There is a great demand for targeted computational techniques to extract information and insights from rich data collections based on clever combinations of human and machine intelligence. We blend elements from fields such as machine learning/AI, probabilistic programming, statistical ecology, and data science, and drive open developer communities that help to translate latest theoretical advances into accessible methods to inform modeling, experimentation, and decision-making. Key applications include microbiome research, population cohort studies, and computational social sciences and humanities (SSH). We also coordinate the Open Knowledge Finland Open Science work group, which received Open Science and Research award of the Ministry of Education and Culture in 2017.
Recent publicationsBelow some examples from recent publications. See ORCID for a full list. Full publication list is also available as bibtex Copies of most papers are available here.
Microbiome data science
Taxonomic signatures of cause-specific mortality risk in human gut microbiome
Salosensaari A, Laitinen V, Havulinna A, Meric G, Cheng S, Perola M, Valsta L, Alfthan G, Inouye M, Watrous JD, Long T, Salido R, Sanders K, Brennan C, Humphrey GC, Sanders JG, Jain M, Jousilahti P, Salomaa V, Knight R, Lahti L, Niiranen T.
Nature Communications 12:2671, May 2021.
Modeling spatial patterns in host-associated microbial communities
Ruuskanen M, Sommeria-Klein G, Havulinna A, Niiranen T, Lahti L.
Environmental Microbiology 23(5), 2021.
Xylo-oligosaccharides in prevention of hepatic steatosis and adipose tissue inflammation: associating taxonomic and metabolomic patterns in fecal microbiomes with biclustering
Hintikka J, Lensu S, Mäkinen E, Karvinen S, Honkanen M, Linden J, Garrels T, Pekkala S, Lahti L.
International Journal of Environmental Research and Public Health 18(8):4049, April 2021.
Statistical and machine learning techniques in human microbiome studies: contemporary challenges and solutions
Frontiers in Microbiology 2021. Moreno-Indias I, Lahti L, Nedyalkova M, Elbere I, Roshchupkin GV, Adilovic M, Aydemir O, Bakir-Gungor B, Carrillo-de Santa Pau E, D’Elia D, Desai MS, Falquet L, Gundogdu A, Hron K, Klammsteiner T, Lopes MB, Marcos Zambrano LJ, Marques C, Mason M, May P, Pašić L, Pio G, Pongor S, Promponas VJ, Przymus P, Sáez-Rodríguez J, Sampri A, Shigdel R, Stres B, Suharoschi R, Truu J, Truică C-O, Vilne B, Vlachakis DP, Yılmaz E, Zeller G, Zomer A, Gómez-Cabrero D, Claesson M.
Links between gut microbiome composition and fatty liver disease in a large population sample
Gut Microbes 2021.
Ruuskanen MO, Åberg F, Männistö V, Havulinna AS, Méric G, Liu Y, Loomba R, Vázquez-Baeza Y, Tripathi A, Valsta LM, Inouye M, Jousilahti P, Salomaa V, Jain M, Knight R, Lahti L, Niiranen TJ.
Microbial communities as dynamical systems
Current Opinion in Microbiology 2018.
Gonze D, Coyte KZ, Lahti L, Faust K.
Signatures of ecological processes in microbial community time series
Faust K, Bauchinger F, Laroche B, de Buyl S, Lahti L, Washburne AD, Gonze D, Widder S.
Multi-stability and the origin of microbial community types
ISME Journal 2017.
Faust K, Gonze D, Lahti L, Raes J.
Linking statistical and ecological theory: Hubbell’s unified neutral theory of biodiversity as a hierarchical Dirichlet process
Proceedings of the IEEE 2017.
Harris K, Parsons TL, Ijaz UZ, Lahti L, Holmes I, Quince C.