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Complex microbial ecosystems multiscale modelling: mechanistic and data driven approaches integration.

Project description

Big Data comes to Europe’s small dairy farms

Brie, mozzarella, feta, cheddar and so many more – European dairy farms produce some of the best and most well-known cheeses in the world, many protected by law as geographical indications or traditional specialties. The European dairy industry plays an important role in European culture and its economy, and its long and successful history is often rooted in traditions passed down over generations. Experience and intuition will soon have a third pillar of support with multiscale modelling tools under development in the context of the EU-funded E-MUSE project. Scientists are harnessing sophisticated biological, statistical and machine learning tools to enable prediction of macro-scale product properties from molecular-scale information related to the complex microbial ecosystems integral to the dairy industry.


European dairy industry is an important agri-food sector; it represents more than 300,000 jobs and 10 billion € positive trade balance. Five out of the ten top global dairy companies are European and more than 80% of European companies are SMEs. More than 300 cheeses and dairy products are sold all over the world and are protected as geographical indications or traditional specialties. Mastering cheese-ripening processes to avoid sanitary risk and waste, and produce typical cheeses with organoleptic properties valued by the consumers is of economic and social significance. E-MUSE aims to develop innovative modelling methodologies to improve knowledge about complex biological systems and to control and/or predict their evolution by combining artificial intelligence and systems biology. This multidisciplinary strategy integrating genome-scale metabolic models, dynamic modelling methodologies, together with the design of efficient statistical and machine learning tools, will allow analysing of multi-omics data and linking the results to macro-scale properties related to cheese ripening and consumer preference. Bioinformatics has addressed this issue by data mining; however, a gap still exists between the molecular scale information and the macroscopic properties that E-MUSE will contribute to fill. Moreover, in the context of sustainable development, more and more consumers are diversifying their diet and consume plant-based food. Introduction of plant-based proteins in the cheese process brings issues such as bitterness or safety. Modelling strategies from the E-MUSE project will help to target and solve these issues. Finally, E-MUSE will train researchers with multidisciplinary skills in mathematics, bioinformatics and/or biology to design and use innovative multiscale modelling methodologies, with the ultimate outcome of a dynamic modelling software giving researchers a harmonised language to address future research questions about complex biological systems.


Net EU contribution
€ 824 406,12
75007 Paris

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Ile-de-France Ile-de-France Paris
Activity type
Research Organisations
Total cost
€ 824 406,12

Participants (9)