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A Robustness Analysis of Dynamic Boolean Models of Cellular Circuits

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Bioinformatics Research and Applications (ISBRA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 11490))

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Abstract

With ever growing amounts of omics data, the next challenge in biological research is the interpretation of these data to gain mechanistic insights about cellular function. Dynamic models of cellular circuits that capture the activity levels of proteins and other molecules over time offer great expressive power by allowing the simulation of the effects of specific internal or external perturbations on the workings of the cell. However, the study of such models is at its infancy and no large scale analysis of the robustness of real models to changing conditions has been conducted to date. Here we provide a computational framework to study the robustness of such models using a combination of stochastic simulations and integer linear programming techniques. We apply our framework to a large collection of cellular circuits and benchmark the results against randomized models. We find that the steady states of real circuits tend to be more robust in multiple aspects compared to their randomized counterparts.

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Notes

  1. 1.

    The source code used for the analysis can be found at github.com/arielbro/attractor_learning, commit hash 83474950c9fc3aa61277d5535a142aad90ff7eed.

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Acknowledgements

RS was supported by a research grant from the Israel Science Foundation (no. 715/18).

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Authors and Affiliations

  1. Blavatnik School of Computer Science, Tel Aviv University, 69978, Tel Aviv, Israel

    Ariel Bruner & Roded Sharan

Authors
  1. Ariel Bruner
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  2. Roded Sharan
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Corresponding author

Correspondence to Roded Sharan .

Editor information

Editors and Affiliations

  1. Georgia State University, Atlanta, GA, USA

    Zhipeng Cai

  2. Georgia State University, Atlanta, GA, USA

    Pavel Skums

  3. Central South University, Changsha, China

    Min Li

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Supplementary material 1 (pdf 62 KB)

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Bruner, A., Sharan, R. (2019). A Robustness Analysis of Dynamic Boolean Models of Cellular Circuits. In: Cai, Z., Skums, P., Li, M. (eds) Bioinformatics Research and Applications. ISBRA 2019. Lecture Notes in Computer Science(), vol 11490. Springer, Cham. https://doi.org/10.1007/978-3-030-20242-2_16

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  • DOI: https://doi.org/10.1007/978-3-030-20242-2_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20241-5

  • Online ISBN: 978-3-030-20242-2

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