ERC Starting Grant · 2024
Unravelling Signalling Heterogeneity using DEEP Learning and MECHANIstic Modelling
Signalling enables cells to respond to external cues, but the inherent heterogeneity of individual cell responses, essential for multicellular organization, complicates disease treatment. Heterogeneity arises from drivers at system and molecular scales, intertwined through feedback loops, making quantitative understanding and prediction challenging. I will address this by pioneering transformative computational methods that predict phospho-signalling responses by integrating deep learning with mechanistic modelling to integrate systems and molecular scales. By using unbiased pattern recognition of deep learning models, I will learn cell states and simple phosphorylation rate laws. These…
From the public funding record at EU CORDIS. Describes the funded project, not the reviews below.