2023/12/10 by David B. Brückner, Gašper Tkačik, Brückner, David B. +1 · 5 citations
Agricultural and Biological Sciences · Biochemistry, Genetics and Molecular Biology · Engineering · #Adaptation and Self-Organizing Systems (nlin.AO) #Biological Physics (physics.bio-ph) #Cell Image Analysis Techniques #Cephalopods and Marine Biology #FOS: Biological sciences #FOS: Physical sciences #Modular Robots and Swarm Intelligence #Pattern Formation and Solitons (nlin.PS) #Statistical Mechanics (cond-mat.stat-mech) #Tissues and Organs (q-bio.TO)
paper · pdf · doi:10.48550/arxiv.2312.05895
openalex publication_date 2023/12/10 · openalex created_date 2023/12/13 · openalex updated_date 2026/07/31
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 a new 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 towards a classification of developmental systems based on a common information-theoretic language, thereby organizing the zoo of implicated chemical and mechanical signaling processes.