Advancing microbiome research with machine learning: key findings from the ML4Microbiome COST action
- Domenica D’Elia
- , Jaak Truu
- , Leo Lahti
- , Magali Berland
- , Georgios Papoutsoglou
- , Michelangelo Ceci
- , Aldert Zomer
- , Marta B. Lopes
- , Eliana Ibrahimi
- , Aleksandra Gruca
- , Alina Nechyporenko
- , Marcus Frohme
- , Thomas Klammsteiner
- , Enrique Carrillo de Santa Pau
- , Laura Judith Marcos-Zambrano
- , Karel Hron
- , Gianvito Pio
- , Andrea Simeon
- , Ramona Suharoschi
- , Isabel Moreno-Indias
- National Research Council of Italy
- University of Tartu
- University of Turku
- Université Paris-Saclay
- Foundation for Research and Technology-Hellas
- University of Crete
- University of Bari
- Utrecht University
- NOVA University Lisbon
- University of Tirana
- Silesian University of Technology
- Kharkiv National University of Radio Electronics
- Technical University of Applied Sciences Wildau
- University of Innsbruck
- IMDEA Food Institute
- Palacký University Olomouc
- University of Novi Sad
- University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca
- Hospital Universitari Virgen de la Victoria
- Sofia University St. Kliment Ohridski
- National University of Science and Technology POLITEHNICA Bucharest
- University of Bergen
- Sarajevo School of Science and Technology
- Swedish University of Agricultural Sciences
- Nicolaus Copernicus University in Toruń
- International Centre for Genetic Engineering and Biotechnology
- Verlab Research Institute for Biomedical Engineering
- Swiss Institute of Bioinformatics
- Polytechnic University of Valencia
- University of Cambridge
- University of Catania
- SS Cyril and Methodius University in Skopje
- Slovak Academy of Sciences
- National Institute for Health and Welfare
- University of Helsinki
- Biome Diagnostics GmbH
- Institute of Science and Technology Austria
Research output: Contribution to journal › Article › peer-review