ArticleProceedings of the National Academy of Sciences of the United States of America2024
Information content and optimization of self-organized developmental systems.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Fundamental limits incorporating logical reasoning into Shannon's information theory.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Position-dependent feedback drives scaling and robustness of morphogen gradients.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Positional information and information flows in dynamic tissues.bioRxiv : the preprint server for biology · 2026Article
- Review
- Optimality as a framework for understanding developmental robustness.Trends in cell biology · 2026Review
- Entropy Bathtub for Living Systems: A Markovian Perspective.Entropy (Basel, Switzerland) · 2026Article
- Dynamical systems of fate and form in development.Seminars in cell & developmental biology · 2025Review
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Authors and funding
2 authors.
Funding
Abstract
A key feature of many developmental systems is their ability to self-organize spatial patterns of functionally distinct cell fates. To ensure proper biological function, such patterns must be established reproducibly, by controlling and even harnessing intrinsic and extrinsic fluctuations. While the relevant molecular processes are increasingly well understood, we lack a principled framework to quantify the performance of such stochastic self-organizing systems. To that end, we introduce an information-theoretic measure for self-organized fate specification during embryonic development. We show that the proposed measure assesses the total information content of fate patterns and decomposes it into interpretable contributions corresponding to the positional and correlational information. By optimizing the proposed measure, our framework provides a normative theory for developmental circuits, which we demonstrate on lateral inhibition, cell type proportioning, and reaction-diffusion models of self-organization. This paves a way toward a classification of developmental systems based on a common information-theoretic language, thereby organizing the zoo of implicated chemical and mechanical signaling processes.
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Registered trials
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