About CAFE-BIO

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This information was extracted from the CORDIS fact sheet.

Understanding complex problems in biological systems

A key challenge is understanding dense, many-body systems with complex interactions under noisy, non-equilibrium biological conditions. A unified framework is needed to integrate approaches from statistical physics. Supported by the Marie Skłodowska-Curie Actions programme, the CAFE-BIO project will provide training aimed at addressing problems in biological systems by integrating methods from diverse scientific fields. The focus will be on individual research projects that incorporate this knowledge in innovative ways. Additionally, the project will deepen understanding of the physical interactions within biological systems, establish quantitative links between microscopic and macroscopic effects, and address real-world complexities through data-driven modelling and experiments. The findings will have critical applications in cancer growth, cardiac health, biofilm formation, and animal fertility.

Objective

This network will provide a rigorous training in solving complex problems in the context of emergence in biological systems, combining approaches from many scientific traditions. A major scientific challenge lies in understanding how dense many-body systems with complex interactions behave at the macroscopic scale under noisy non-equilibrium biological conditions. A coherent framework for performing such an analysis, grounded in the principles of statistical physics, demands an integration of multiple approaches that are currently applied in isolation and in a fragmented fashion. This network will build this coherence, by bringing together multiple partners with substantial complementary expertise, and through individual research projects that are each designed to combine this expertise in fundamentally new ways. Through this, we will gain new understanding of the novel physical interactions that biological systems create, establish quantitative relationships between microscopic interactions and macroscopic collective effects, and confront the complexity of real-world systems through data-driven modelling and experimental applications. This new understanding has a range of important applications, including cancer growth, cardiac health, biofilm formation and animal fertility.

The research training will be complemented by professional training in advanced digital skills, such as software and data carpentry, as well as in entrepreneurship, communication and public engagement, much of which will be delivered through non-academic partnerships. All doctoral candidates will complete academic or non-academic secondments for a substantial period. These experiences will fill transferable skills gaps in traditional doctoral research training, and build doctoral candidates’ career prospects and the European skills base in the digital economy. Lasting elements of the programme include this novel training, and a series of public engagement activities that will be created.