CORDIS Project
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This project develops computational methods that integrate machine learning and dynamical systems to analyze single-cell data. It aims to uncover the complex interactions and mechanisms within tissues, enhancing our understanding of cellular identity and behavior in health and disease.
Advances in technologies that measure gene expression at single-cell resolution have revolutionized our understanding of the heterogeneity, structure and dynamics of tissues and whole organisms in health and disease.
Yet, in most single-cell experiments tissue structure, temporal trajectories, and their underlying mechanisms are lost or not directly accessible.
Despite experimental advances, major gaps remain in understanding how tissues orchestrate multicellular functions.
In recent years, we a…
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