Advances in Generative Models for Morphogenesis in Developmental Biology

Morphogenesis is the biological process by which cells, tissues, and organs acquire their shape, it is a fundamental aspect of development. Understanding how genetic, biochemical, and mechanical cues converge to orchestrate these complex patterns remains one of the central challenges in developmental biology. In recent years, advances in computational power and artificial intelligence have opened new opportunities to model and predict morphogenetic processes with unprecedented accuracy.Generative models, including deep learning frameworks, physics-informed neural networks, and agent-based simulations, provide powerful tools to capture the dynamic and multiscale nature of morphogenesis. By integrating high-resolution imaging, single-cell omics, and biomechanical data, these models can replicate tissue patterning, growth, and differentiation in silico. Importantly, they do not only describe developmental processes but also generate novel hypotheses about the mechanisms that drive self-organization.This Research Topic aims to bring together innovative contributions that leverage generative models to advance our understanding of morphogenesis. We welcome studies that combine experimental and computational approaches, explore emergent properties of cellular collectives, and highlight how generative modeling can bridge the gap between genotype and phenotype. Areas of interest include, but are not limited to:• Generative models for tissue and organ development• Data-driven simulations of cell migration, proliferation, and differentiation• Multiscale frameworks linking molecular regulation to tissue-level architecture• Integration of biomechanics and biophysics in generative morphogenetic models• Applications in regenerative medicine, organoids, and synthetic biologyBy showcasing interdisciplinary research, this collection will emphasize the transformative role of generative models in unraveling the principles of development. Ultimately, it seeks to inspire novel strategies for manipulating morphogenetic processes in health, disease, and bioengineering applications. Topic editors: Susan Mertins, Michael Blinov, Paul Macklin, Daniel Lobo Source: https://www.frontiersin.org/research-topics/74583/advances-in-generative-models-for-morphogenesis-in-developmental-biology