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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

van der Zee, Lucas and Barberis, Matteo (2019) Advanced Modeling of Cellular Proliferation: Toward a Multi-scale Framework Coupling Cell Cycle to Metabolism by Integrating Logical and Constraint-Based Models Methods in Molecular Biology, 2049. pp. 365-385.

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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.

Item Type: Article
Divisions : Faculty of Health and Medical Sciences > School of Biosciences and Medicine
Authors :
NameEmailORCID
van der Zee, Lucas
Barberis, Matteom.barberis@surrey.ac.uk
Date : 11 October 2019
DOI : 10.1007/978-1-4939-9736-7_21
Copyright Disclaimer : © Springer Science+Business Media, LLC, part of Springer Nature 2019
Uncontrolled Keywords : Cell cycle; Constraint-based modeling; Logical modeling; Metabolism; Multi-scale modeling and simulation; Systems biology.
Depositing User : James Marshall
Date Deposited : 18 Jun 2020 10:17
Last Modified : 18 Jun 2020 10:17
URI: http://epubs.surrey.ac.uk/id/eprint/858021

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