The Growing Canvas of Biological Development: Multiscale Pattern Generation on an Expanding Lattice of Gene Regulatory Nets

  • René Doursat


The spontaneous generation of an entire organism from a single cell is the epitome of a self-organizing, decentralized complex system. How do nonspatial gene interactions extend in 3-D space? In this work, I present a simple model that simulates some biological developmental principles using an expanding lattice of cells. Each cell contains a gene regulatory network (GRN), modeled as a feedforward hierarchy of switches that can settle in various on/off expression states. Local morphogen gradients provide positional information in input, which is integrated by each GRN to produce differential expression of identity genes in output. Similarly to striping in the Drosophila embryo, the lattice becomes segmented into spatial regions of homogeneous genetic expression that resemble stained-glass motifs. Meanwhile, it also expands by cell proliferation, creating new local gradients of positional information within former single-identity regions. Analogous to a “growing canvas” painting itself, the alternation of growth and patterning results in the creation of a form. This preliminary study attempts to reproduce pattern formation through a multiscale, recursive and modular process. It explores the elusive relationship between nonspatial GRN weights (genotype) and spatial patterns (phenotype). Abstracting from biology in the same spirit as neural networks or swarm optimization, I hope to be contributing to a novel engineering paradigm of system construction that could complement or replace omniscient architects with decentralized collectivities of agents.


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  1. [1]
    Carroll, S. B., Grenier, J. K., & Weatherbee, S. D., 2001, From DNA to Diversity, Blackwell Scientific (Maiden, MA).Google Scholar
  2. [2]
    Coen, E., 2000, The Art of Genes, Oxford University Press.Google Scholar
  3. [3]
    Edelman, G. M., 1988, Topobiology, Basic Books.Google Scholar
  4. [4]
    Braha, D., Bar-Yam, Y., & Minai, A. A. (ed.), 2006, Complex Engineered Systems: Science Meets Technology, Springer Verlag.Google Scholar
  5. [5]
    Mjolsness, E., Sharp D. H., & Reinitz, J., 1991, A connectionist model of development, Journal of Theoretical Biology, 152: 429–453.CrossRefGoogle Scholar
  6. [6]
    Nagpal, R., 2002, Programmable self-assembly using biologically-inspired multi-agent control, 1st Int Conf on Auton Agents, July 15–19, Bologna, Italy.Google Scholar
  7. [7]
    Salazar-Ciudad, I., Garcia-Fernández, J., & Solé, R., 2000, Gene networks capable of pattern formation, Journal of Theoretical Biology, 205: 587–603.CrossRefGoogle Scholar
  8. [8]
    Schlosser, G., & Wagner, G. P. (ed.), 2004, Modularity in Development and Evolution, The University of Chicago Press.Google Scholar
  9. [9]
    von Dassow, G., Meir, E., Munro, E. M., & Odell, G. M., 2000, The segment polarity network is a robust developmental module, Nature, 406: 188–192.ADSCrossRefGoogle Scholar
  10. [10]
    Wolpert, L., 1969, Positional information and the spatial pattern of cellular differentiation development, Journal of Theoretical Biology, 25: 1–47.CrossRefGoogle Scholar

Copyright information

© Springer 2010

Authors and Affiliations

  • René Doursat
    • 1
  1. 1.Department of Computer Science and EngineeringUniversity of NevadaReno

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