In recent years, the scientific community has increasingly recognized that the complexity inherent in biological systems cannot be understood simply by examining their individual components in isolation. Instead, these systems exhibit emergent properties—dynamic behaviors and functionalities arising from intricate interactions amongst molecules, cells, and tissues. Addressing this profound challenge, a new international doctoral training network, aptly named “Coherent Analysis Framework for Emergence in Biological Systems” (CAFE-BIO), is set to transform how theoretical perspectives on biological complexity are developed. Spearheaded by an alliance of leading European institutions, including the University of Göttingen, the Max Planck Institute for Dynamics and Self-Organization (MPI-DS), and the University of Edinburgh, this network has been awarded €4.5 million through the prestigious Marie Skłodowska-Curie Actions program, reflecting the European Union’s commitment to advancing fundamental research at the interface of physics and biology.
The CAFE-BIO network represents a paradigm shift in doctoral research training by emphasizing interdisciplinary collaboration and integrative modeling approaches. It brings together a coalition of twelve prominent universities and research centers across Europe, complemented by engagement with industry partners, to precisely train the next generation of scientists. Fifteen PhD researchers will be recruited, each immersed in cutting-edge theoretical frameworks designed to unravel the multifaceted nature of biological systems. What distinguishes this initiative is the innovative mandate for each researcher to collaborate with experts from two distinct academic institutions. This strategy aims to synergize diverse methodologies and theoretical traditions that were formerly pursued in parallel, thereby fostering novel insights not achievable in isolation.
A cornerstone of CAFE-BIO involves developing and applying models rooted in physics but radically adapted to capture the unique behaviors of living matter. For example, the research group led by the University of Barcelona is pioneering efforts to model dense active matter systems, which are assemblies of self-driven units, like cells, that continually consume energy to generate movement and mechanical stresses. Unlike classical condensed matter, living systems exhibit non-equilibrium dynamics and interactions that require reformulations of theoretical physics principles. By formulating mathematically rigorous descriptions of such active materials, this group aims to elucidate how cellular assemblies collectively behave and organize, addressing long-standing questions in tissue dynamics and morphogenesis.
Complementing this theoretical journey, a second team headed by Leiden University focuses on translating microscopic interactions into emergent macroscopic phenomena observable at the organismal scale. This entails developing novel computational and analytical tools that robustly link molecular-scale information to system-level functionality—a notoriously difficult “upscaling” problem. By uncovering how local cell-cell interactions and internal regulations manifest as coherent behaviors visible to the naked eye, researchers are working towards predictive frameworks capable of explaining phenomena such as tissue elasticity, shape transformations, and responsiveness to environmental stimuli.
Meanwhile, Warsaw University is harnessing the power of state-of-the-art machine learning to refine and accelerate the design of predictive models. The complexity of biological data and the nonlinear multi-dimensional aspects of system dynamics pose significant challenges to conventional analytical techniques. Advanced algorithms based on deep learning and other artificial intelligence modalities are uniquely suited to extract hidden patterns and infer governing equations from experimental datasets. The integration of these computational approaches with physics-based theory holds the promise of radically improving model accuracy and predictive power, enabling unprecedented understanding and control of biological complexity.
What unites these diverse strands of research under the CAFE-BIO banner is the commitment to an overarching framework grounded in fundamental physics principles but tailored explicitly for biological realities. This framework aspires to systematically characterize emergent phenomena, such as self-organization and collective behavior, spanning scales from subcellular to organismal. Such advances will not only deepen conceptual knowledge but also provide practical paradigms for bioengineering, synthetic biology, and medical diagnostics, where the ability to predict and manipulate complex biological systems is indispensable.
The doctoral researchers’ training experience will be further enriched through collaborations with partners beyond academia, including entities like IndiScale—a spinoff company originating from MPI-DS dedicated to the management and reproducibility of research data. These interactions ensure that students gain expertise in modern data stewardship practices crucial for transparency and scientific rigor. Moreover, the exposure to industrial and applied contexts equips them with versatile skills applicable across sectors, enhancing employability and impact.
The geographic and institutional configuration of the network features Göttingen and Edinburgh as central hubs, capitalizing on their exceptional existing research infrastructures and expertise. Five principal investigators from Göttingen contribute profound insights spanning theoretical physics, systems biology, and complex systems dynamics. At the University of Göttingen’s Institute of Theoretical Physics and MPI-DS, scientists like Professors Stefan Klumpp and Peter Sollich, as well as Dr. Philip Bittihn, lead cutting-edge inquiries that form the backbone of CAFE-BIO’s theoretical ambitions. Their coordinated efforts, together with contributions from Edinburgh and other partners, architect a collaborative ecosystem fostering intellectual cross-pollination and innovation.
The Marie Skłodowska-Curie Actions funding underlines the European Union’s strategic vision to cultivate scientific excellence through cross-border collaboration and interdisciplinary research. This initiative represents a significant investment in the future of complex systems biology, recognizing that breakthroughs in understanding life’s complexity rest on the integration of physics, mathematics, computer science, and biology. Seed money from the Ministry for Science and Culture of Lower Saxony and the Royal Society of Edinburgh initially catalyzed this partnership, exemplifying how regional and national support can accelerate world-class science.
From autumn 2026 onwards, recruitment will open doors for a new cohort of doctoral candidates ready to engage deeply with the problems of biological emergence. These young scientists will partake in a meticulously designed research and training program encompassing theoretical foundations, computational methods, and experimental collaborations. The interdisciplinary environment nurtures creativity and critical thinking, fostering innovative solutions to some of the most challenging questions at this scientific frontier.
At its core, CAFE-BIO embodies a visionary approach to training that positions early-career researchers at the convergence of theory and application. The intricate dance of molecules and cells inside organisms gives rise to life in all its diversity and adaptability, yet fully deciphering these phenomena has remained elusive. By embracing coherence in analysis and fostering collective intellectual efforts spanning borders and disciplines, this doctoral network aims to illuminate the physical underpinnings of biological complexity, potentially revolutionizing our understanding and manipulation of living systems.
As this ambitious program gets underway, it provides a beacon highlighting the fruitful intersection of physics and biology. Its success may well catalyze future generations of researchers who will transcend conventional boundaries, leveraging the power of integrated theoretical frameworks and computational advances to unlock the secrets of life’s emergent phenomena. The world watches with anticipation as CAFE-BIO prepares to contribute substantially to the scientific narrative describing how the complexity of life unfolds from the cooperative interplay of its fundamental constituents.
Subject of Research: Emergence in Complex Biological Systems through Theoretical and Computational Modeling
Article Title: Advancing Theoretical Frontiers in Biological Complexity: The Launch of the CAFE-BIO Doctoral Network
News Publication Date: Not specified
Web References:
– University of Göttingen: http://www.uni-goettingen.de/en/583011.html
– Professor Peter Sollich profile: http://www.uni-goettingen.de/en/583011.html
– Professor Stefan Klumpp profile: http://www.uni-goettingen.de/en/527801.html
– Dr. Philip Bittihn profile: http://www.ds.mpg.de/lmp/bittihn
Image Credits: Leila Abbaspour
Keywords: Biological models, Physics, Theoretical physics, Mathematical modeling, Complex systems, Dynamics, Biophysics, Cell biology, Cell models, Modeling, Computational biology
