Marr's Three Levels for Embryonic Development: Information, Dynamical Systems, Gene Networks

Developmental patterning comprises processes that range from purely instructed, where external signals specify cell fates, to fully self-organized, where spatial patterns emerge autonomously through cellular interactions. We propose that both extremes—as well as the continuum of intermediate cases—can be conceptualized as information-processing systems, whose operation can be described using “Marr's three levels of analysis”: the computational problem being solved, the algorithms employed, and their molecular implementation. At the first level, we argue that normative theories, such as information-theoretic optimization principles, provide a formalization of the computational problem. At the second level, we show how simplified information-processing architectures provide a framework for developmental algorithms, which are formalized mathematically using dynamical systems theory. At the third level, the implementation of developmental algorithms is described by mechanistic biophysical and gene regulatory network models.

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Publication Details

Journal
PRX Life
Published
2025-12-23
DOI
https://doi.org/10.1103/fdcf-dkws
Primary Topic
Gene Regulatory Network Analysis
Type
article
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article

Marr's Three Levels for Embryonic Development: Information, Dynamical Systems, Gene Networks

G. Tkačik, Anonymous
PRX Life
Gene Regulatory Network Analysis
article

Marr's Three Levels for Embryonic Development: Information, Dynamical Systems, Gene Networks

G. Tkačik, Anonymous
article en

Abstract

Developmental patterning comprises processes that range from purely instructed, where external signals specify cell fates, to fully self-organized, where spatial patterns emerge autonomously through cellular interactions. We propose that both extremes—as well as the continuum of intermediate cases—can be conceptualized as information-processing systems, whose operation can be described using “Marr's three levels of analysis”: the computational problem being solved, the algorithms employed, and their molecular implementation. At the first level, we argue that normative theories, such as information-theoretic optimization principles, provide a formalization of the computational problem. At the second level, we show how simplified information-processing architectures provide a framework for developmental algorithms, which are formalized mathematically using dynamical systems theory. At the third level, the implementation of developmental algorithms is described by mechanistic biophysical and gene regulatory network models.

PRX LifeVol. 4(1)
Institute of Science and Technology Austria (AT), University of Basel (CH)
Openalex Percentile: Top 37%
Gene Regulatory Network Analysis
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