Summary
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.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/956126 |
| Start date: | 01-01-2021 |
| End date: | 30-06-2025 |
| Total budget - Public funding: | 3 901 305,60 Euro - 3 901 305,00 Euro |
Cordis data
Original description
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.Status
SIGNEDCall topic
MSCA-ITN-2020Update Date
28-04-2024
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Organisations
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| INSTITUT NATIONAL DE RECHERCHE POUR L'AGRICULTURE, L'ALIMENTATION ET L'ENVIRONNEMENT (Coördinator)
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| AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS
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| ALMA MATER STUDIORUM-UNIVERSITA DI BOLOGNA
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| CHR. HANSEN A/S
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| KATHOLIEKE UNIVERSITEIT LEUVEN
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| NIZO FOOD RESEARCH BV
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| STICHTING VU
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| SZEGEDI TUDOMANYEGYETEM
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| UNIVERSITA TA MALTA
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| UNIVERSITE PAUL SABATIER TOULOUSE III