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Computational Systems Biology of Morphogenesis

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Computational Systems Biology in Medicine and Biotechnology

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2399))

Abstract

Extracting mechanistic knowledge from the spatial and temporal phenotypes of morphogenesis is a current challenge due to the complexity of biological regulation and their feedback loops. Furthermore, these regulatory interactions are also linked to the biophysical forces that shape a developing tissue, creating complex interactions responsible for emergent patterns and forms. Here we show how a computational systems biology approach can aid in the understanding of morphogenesis from a mechanistic perspective. This methodology integrates the modeling of tissues and whole-embryos with dynamical systems, the reverse engineering of parameters or even whole equations with machine learning, and the generation of precise computational predictions that can be tested at the bench. To implement and perform the computational steps in the methodology, we present user-friendly tools, computer code, and guidelines. The principles of this methodology are general and can be adapted to other model organisms to extract mechanistic knowledge of their morphogenesis.

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Acknowledgments

We thank the members of the Lobo Lab for helpful discussions. This work was supported by the National Institute of General Medical Sciences of the National Institutes of Health under award number R35GM137953. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Author Contributions: J. K. wrote Subheading 3.2. R. M. wrote Subheading 3.3. D. L. wrote Subheadings 1, 3.1, 3.4, and 3.5. All authors revised and approved the final version of the manuscript.

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Authors and Affiliations

  1. Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD, USA

    Jason M. Ko, Reza Mousavi & Daniel Lobo

Authors
  1. Jason M. Ko
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  2. Reza Mousavi
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  3. Daniel Lobo
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Corresponding author

Correspondence to Daniel Lobo .

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Editors and Affiliations

  1. Laboratory of Cardiovascular Science, National Institute on Aging, NIH, Baltimore, MD, USA

    Sonia Cortassa

  2. Translational Gerontology Branch, Laboratory of Cardiovascular Science, National Institute on Aging, NIH, Baltimore, MD, USA

    Miguel A. Aon

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Ko, J.M., Mousavi, R., Lobo, D. (2022). Computational Systems Biology of Morphogenesis. In: Cortassa, S., Aon, M.A. (eds) Computational Systems Biology in Medicine and Biotechnology. Methods in Molecular Biology, vol 2399. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1831-8_14

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  • DOI: https://doi.org/10.1007/978-1-0716-1831-8_14

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1830-1

  • Online ISBN: 978-1-0716-1831-8

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