Complex Multicellular Organism Development

Complex multicellular organism development investigates how single cells organize into intricate tissues and organs. Current research focuses on modeling these processes using geometric deep learning, graph neural networks, and generative transformer models like GPTs, aiming to predict cellular behavior and morphogenesis from both experimental and simulated data. These computational approaches, often leveraging graph representations of cell interactions, are improving our understanding of the underlying mechanisms driving development and hold promise for applications in bioengineering and the design of novel bio-inspired materials. Ultimately, this research seeks to create comprehensive, predictive models of multicellular development, bridging the gap between cellular-level interactions and macroscopic organismal form.