Complex microbial ecosystems multiscale modelling mechanistic and data driven a...
Complex microbial ecosystems multiscale modelling mechanistic and data driven approaches integration.
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 comp...
ver más
¿Tienes un proyecto y buscas un partner? Gracias a nuestro motor inteligente podemos recomendarte los mejores socios y ponerte en contacto con ellos. Te lo explicamos en este video
Proyectos interesantes
PTQ-17-09035
Diseño e implementación de sistemas de aprendizaje automátic...
115K€
Cerrado
PID2019-108829RB-I00
LA BELLEZA DE LO PROFUNDO: APLICACIONES DEL DEEP LEARNING...
Cerrado
DD-DeCaF
Bioinformatics Services for Data Driven Design of Cell Facto...
7M€
Cerrado
TIN2008-06247
DESARROLLO DE NUEVAS TECNICAS DE EXTRACCION DE CONOCIMIENTO...
86K€
Cerrado
RYC-2017-23645
Multiomics and systems biology approaches in grapevine (Viti...
309K€
Cerrado
GLOMICAVE
Global Omic Data Integration on Animal Vegetal and Environm...
6M€
Cerrado
Información proyecto E-MUSE
Duración del proyecto: 58 meses
Fecha Inicio: 2020-08-28
Fecha Fin: 2025-06-30
Fecha límite de participación
Sin fecha límite de participación.
Descripción del proyecto
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.