COST Action ML4Microbiome

COST Actions are research networks funded through The European Cooperation in Science and Technology (COST)

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Our group is involved in the COST Action CA18131 Statistical and machine learning techniques in human microbiome studies (ML4Microbiome), with PI Bertelsen as Vice Chair for the Action.

COST Action ML4Microbiome will create a network for discovery-oriented microbiome researchers and data-driven ML experts through meetings, workshops and training courses. The goal is to optimize and standardize the use of ML for microbiome research. 


D'Elia D, Truu J, Lahti L, Berland M, Papoutsoglou G, Ceci M, Zomer A, Lopes MB, Ibrahimi E, Gruca A, Nechyporenko A, Frohme M, Klammsteiner T, Pau ECS, Marcos-Zambrano LJ, Hron K, Pio G, Simeon A, Suharoschi R, Moreno-Indias I, Temko A, Nedyalkova M, Apostol ES, Truică CO, Shigdel R, Telalović JH, Bongcam-Rudloff E, Przymus P, Jordamović NB, Falquet L, Tarazona S, Sampri A, Isola G, Pérez-Serrano D, Trajkovik V, Klucar L, Loncar-Turukalo T, Havulinna AS, Jansen C, Bertelsen RJ, Claesson MJ. Advancing microbiomerResearch with machine learning: key findings from the ML4Microbiome COST action. Front Microbiol. 2023 Sep 25;14:1257002. doi: 10.3389/fmicb.2023.1257002. eCollection 2023 - access the paper here

Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions. Frontiers in Microbiology (2021) - access the paper here

Applications of Machine Learning in Human Microbiome Studies: A Review on Feature Selection, Biomarker Identification, Disease Prediction and Treatment. Frontiers in Microbiology - access the paper here

COST creates spaces where scientists are in the driving seat (bottom-up) and ideas can grow through a flexible and open approach. By enabling researchers from academia, industry and the public and private sector to work together in open networks that transcend borders, COST helps to advance science, stimulates knowledge sharing and pools resources.