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Advanced Modeling of Cellular Proliferation: Toward a Multi-scale Framework Coupling Cell Cycle to Metabolism by Integrating Logical and Constraint-Based Models

  • Lucas van der Zee
  • Matteo BarberisEmail author
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 2049)

Abstract

Biological functions require a coherent cross talk among multiple layers of regulation within the cell. Computational efforts that aim to understand how these layers are integrated across spatial, temporal, and functional scales represent a challenge in Systems Biology. We have developed a computational, multi-scale framework that couples cell cycle and metabolism networks in the budding yeast cell. Here we describe the methodology at the basis of this framework, which integrates on off-the-shelf logical (Boolean) models of a minimal yeast cell cycle with a constraint-based model of metabolism (i.e., the Yeast 7 metabolic network reconstruction). Models are implemented in Python code using the BooleanNet and COBRApy packages, respectively, and are connected through the Boolean logic. The methodology allows for incorporation of interaction data, and validation through –omics data. Furthermore, evolutionary strategies may be incorporated to explore regulatory structures underlying coherent cross talks among regulatory layers.

Key words

Multi-scale modeling and simulation Systems biology Logical modeling Constraint-based modeling Cell cycle Metabolism 

Notes

Acknowledgments

This work was supported by the Systems Biology Grant of the University of Surrey to M.B., and by the SILS Starting Grant of the University of Amsterdam (UvA) and by the UvA-Systems Biology Research Priority Area Grant to M.B.

Author contribution: M.B. conceived the idea and designed the study. L.v.d.Z. and M.B. designed the computational analyses. L.v.d.Z. programmed the source code and performed the simulations. L.v.d.Z. and M.B. analyzed the data. L.v.d.Z. and M.B. wrote the chapter. M.B. provided scientific leadership and supervised the study.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Systems Biology, School of Biosciences and Medicine, Faculty of Health and Medical SciencesUniversity of SurreyGuildford, SurreyUK
  2. 2.Synthetic Systems Biology and Nuclear Organization, Swammerdam Institute for Life SciencesUniversity of AmsterdamAmsterdamThe Netherlands

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