Report of the ML4Microbiome workshop 2021 - Statistical and Machine Learning Techniques for Microbiome Data Analysis

Eliana Ibrahimi, Ilze Elbere, Magali Berland, Domenica D'Elia


The bacteria living in and on us, over 100 trillion, are essential for human development, immunity and nutrition and ultimately for human health. Researchers awareness of the importance of the microbiome for human wellbeing brought in the latest decade to the flourishing of new and numerous projects focused on the human microbiome, increasing the number of large microbiome datasets available. As a result, statistical and machine learning techniques to solve microbiome data analysis challenges are in high demand. The workshop “Statistical and Machine Learning Techniques for Microbiome Data Analysis” was organised by the COST Action ML4Microbiome to introduce the main concepts of study design and statistical/machine learning techniques used in human microbiome studies to a broad community of researchers and to foster connections between the discovery-oriented microbiome and statistical/machine learning researchers inside and outside the ML4Microbiome COST Action. To this aim, the workshop was organised as part of the training programme of the GOBLET & EMBnet Annual General Meeting 2021. This allowed ML4Microbiome to reach a broad and multidisciplinary community of scientists working in Bioinformatics and Computational Biology research and education from all over the world. The workshop attracted more than 80 participants from 40 different countries. In this paper, we report about the main topics treated and discuss the attendants’ feedback regarding their level of satisfaction and their specific needs/demands for possible improvement of the training offer of ML4Microbiome in the microbiome research field. Under the authors’ permission, presentations were recorded and are available as an ML4Microbiome playlist on YouTube ( The programme and presentations files are available at the ML4Microbiome website (


Microbiome; workshop;

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