Speakers

Title of talk: Mechanistic modelling and machine learning: A love story

Abstract: In the realm of systems biology, the marriage between mechanistic modelling and machine learning has blossomed into a dynamic partnership, revolutionizing our understanding of complex biological systems. This presentation explores the intertwined relationship between mechanistic modelling and machine learning, highlighting their collaborative efforts in unraveling biological mysteries.

One of the key aspects of this love story is the utilization of machine learning methods for the optimization of mechanistic models. By harnessing the power of mini-batch optimisation, the training of comprehensive models for biological processes becomes feasible. Furthermore, the emergence of invertible neural networks has opened new avenues for Bayesian uncertainty analysis in systems biology. These innovative approaches enable researchers to unravel uncertainty in model predictions, providing deeper insights, e.g. into biological variability.

A second key aspect is the incorporation of biological priors in machine learning models and the formulation of hybrid models. This adds another layer of sophistication to this love story. By integrating prior knowledge derived from biological principles, machine learning algorithms can better adapt to the complexities and nuances of biological data, enhancing the predictive accuracy and interpretability of models.

Through a series of examples, this presentation will showcase the symbiotic relationship between mechanistic modelling and machine learning, demonstrating how their combined efforts are driving forward our understanding of complex biological systems and paving the way for future advancements in systems biology research.

Jan Hasenauer in short: Jan Hasenauer studied Technical Cybernetics at the University of Stuttgart, where he also obtained his doctoral degree in Engineering Sciences. He then worked at the Helmholtz Zentrum München and the Technical University of Munich as PostDoc and leader of a Young investigator group. Since 2017, he has been a Professor of Mathematics and Life Sciences at the University of Bonn, and since 2022, he has held one of the highly prestigious Schlegel professorships established within the framework of the Excellence Initiative. Jan Hasenauer received several awards, including the MTZ Award for Medical Systems Biology and is a member of the Excellence Clusters “Hausdorff Center for Mathematics” and “ImmunoSensation2” of the University of Bonn.

https://www.mathematics-and-life-sciences.uni-bonn.de/en/research/hasenauer-group

Director of the Molecular Epidemiology Laboratory and leader of the Molecular Epidemiology (MEL) research team.

https://www.qmul.ac.uk/wiph/people/profiles/nedjai-belinda.html

Title of talk: Bioprinting models of the human heart at CÚRAM, the Research Ireland Centre for Medical Devices

Abstract: Engineered biomaterials are enabling progress in numerous medical fields, ranging from medical device development to tissue engineering. This talk will provide an overview of CÚRAM, the Research Ireland Centre for Medical Devices at the University of Galway, and highlight its interdisciplinary approach to accelerating the translation of medical device research into impactful clinical solutions. I’ll then focus on my own research lab within CÚRAM, where we specialize in bioprinting models of the human heart. I’ll describe how incorporating principles of heart development into bioprinting strategies can enhance cell and tissue maturation, thereby enhancing physiological relevance for disease modelling, drug screening, and regenerative medicine applications.

Andrew Daly in short: Dr Andrew Daly is an Associate Professor in Biomedical Engineering at the University of Galway and a Principal Investigator at CÚRAM, the Research Ireland Centre for Medical Devices. He holds a BAI and PhD in Mechanical Engineering from Trinity College Dublin, Ireland. After a postdoctoral fellowship at the University of Pennsylvania, Dr. Daly returned to Ireland to establish his independent research group at the University of Galway. His highly-cited work has been published in leading journals such as Nature Communications, Nature Reviews Materials, Cell, and Biomaterials. He has secured over €2.4 million in research funding, including a prestigious European Research Council Starting Grant in 2022.

https://www.universityofgalway.ie/science-engineering/staff-profiles/andrewdaly/

https://www.biofabrication.ie/

Title of talk: Decoding biological aging and frailty with AI and multiomics

Abstract: Biological age estimates how well our bodies are functioning compared to our chronological age. There are various ways to measure biological age at the cellular, organ, and system-wide levels, all of which offer insights into disease risk and mortality beyond chronological age. My group focuses on uncovering the drivers of biological aging using omics and causal inference approaches, and developing a system-wide biological aging measure for healthcare: the electronic frailty index.

Juulia Jylhävä in short: Juulia Jylhävä is a senior research fellow at the Institute for Advanced Study, Tampere, and a leader of the Systems Biology of Aging groups a Tampere University, Finland, and Karolinska Institutet, Stockholm, Sweden. She is passionate about unraveling the causes and consequences of biological aging, exploring its alignment with age-related diseases and discovering ways to promote healthier aging.

Systems Biology of Aging – BioAge

Biophysics of the eye