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Advances in Unconventional Computing pp 637–654Cite as

Computing a Worm: Reverse-Engineering Planarian Regeneration

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Part of the book series: Emergence, Complexity and Computation ((ECC,volume 23))

Abstract

In order to understand and control complex biological systems, we need to unravel the information processing and computations required to regulate their dynamics. The development of a complete organism from a single cell or the restoration of lost structures and body parts after amputations require the coordination of millions of cells exchanging and processing information. Understanding these dynamic processes from the results of biological perturbation experiments represent an outstanding challenge due to the characteristic non-linear dynamics and feed-back loops of their molecular and biophysical regulatory mechanisms—an inverse problem with no analytical or computationally tractable solutions. To bridge the gap between molecular-level mechanistic data and systems-level outcomes, we have developed a computational methodology based on heuristic algorithms to automatically reverse-engineer dynamic regulatory networks directly from experimental results. Using this method, applied to problems of pattern regulation during metazoan regeneration, we inferred the first comprehensive regulatory network of planarian regeneration, capable of explaining the most relevant experiments of anterior-posterior specification during regeneration. Here we summarize our results and study the dynamics of the inferred regulatory model, unraveling the information processing and computations required to regenerate a correct morphology.

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Acknowledgments

This work was supported by NSF grant EF-1124651, NIH grant GM078484, USAMRMC grant W81XWH-10-2-0058, and the Mathers Foundation. Computation used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by NSF grant ACI-1053575, and a cluster computer awarded by Silicon Mechanics.

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  1. Department of Biological Sciences, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD, 21250, USA

    Daniel Lobo

  2. Department of Biology, Center for Regenerative and Developmental Biology, Tufts University, 200 Boston Avenue, Suite 4600, Medford, MA, 02155, USA

    Michael Levin

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  1. Unconventional ComputingCentre, University of the Westof England Unconventional ComputingCentre, Bristol, United Kingdom

    Andrew Adamatzky

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Lobo, D., Levin, M. (2017). Computing a Worm: Reverse-Engineering Planarian Regeneration. In: Adamatzky, A. (eds) Advances in Unconventional Computing. Emergence, Complexity and Computation, vol 23. Springer, Cham. https://doi.org/10.1007/978-3-319-33921-4_24

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  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-33920-7

  • Online ISBN: 978-3-319-33921-4

  • eBook Packages: EngineeringEngineering (R0)

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