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КартаВръзкиТемиБългарияНощта (K-TRIO)Мария Склодовска-КюриЗа ученициЗа учителиМетодологияИзненадай ме
H2020Докторантска мрежа2021–2025

E-MUSE · Complex microbial ecosystems multiscale modelling: mechanistic and data driven approaches integration.

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период
2021-01-01 → 2025-06-30
Финансиране от ЕС
3 901 306 €
Участници
10
Схема
MSCA-ITN

Линиите свързват координатора с партньорите.

Накратко на български

Микробните общности в ферментиралите продукти се анализират чрез математически модели и данни, за да се разбере структурата и развитието им. Това помага за създаването на по-безопасни храни, устойчиво производство на биосъединения и развитието на зелената химия.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

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

There is a bottleneck in the methodologies for extracting meaningful results from high-throughput data analyses of complex biological systems, in part due to a still underdeveloped interdisciplinary interaction between biologists, mathematicians, and computer scientists. With E-MUSE, Europe is at the forefront of these methodologies, which impact many domains linked to societal and economic challenges, like novel and more controlled methods for safe and tasty food production, applications in green chemistry to predict the evolution of microbial ecosystems for bioconversion processes or in sustainable development for bio-compound production. The research programme of the E-MUSE network was to develop innovative methodologies, combining mechanistic and data-driven approaches, to model structural and dynamic features of microbial communities, to identify key processes and biomarkers for specific applications. The early-stage researchers (ESRs) with biology, mathematics or modelling projects have interacted to understand the structure and function of microbial communities involved in fermented products and predict their evolution.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

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.

Оригинален текст от CORDIS (на английски).

Участници

Връзки

Данни: CORDIS, © Европейски съюз