期刊
BIOINFORMATICS
卷 29, 期 24, 页码 3181-3190出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btt552
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资金
- Biotechnology and Biological Sciences Research Council [BB/I008195/1]
- Era SysBioPlus TB-HOST-NET grant [BB/I00453X/1]
- BBSRC [BB/I00453X/1, BB/I008195/1] Funding Source: UKRI
- Biotechnology and Biological Sciences Research Council [BB/I00453X/1, BB/I008195/1] Funding Source: researchfish
Motivation: Dynamic simulation of genome-scale molecular interaction networks will enable the mechanistic prediction of genotype-phenotype relationships. Despite advances in quantitative biology, full parameterization of whole-cell models is not yet possible. Simulation methods capable of using available qualitative data are required to develop dynamic whole-cell models through an iterative process of modelling and experimental validation. Results: We formulate quasi-steady state Petri nets (QSSPN), a novel method integrating Petri nets and constraint-based analysis to predict the feasibility of qualitative dynamic behaviours in qualitative models of gene regulation, signalling and whole-cell metabolism. We present the first dynamic simulations including regulatory mechanisms and a genome-scale metabolic network in human cell, using bile acid homeostasis in human hepatocytes as a case study. QSSPN simulations reproduce experimentally determined qualitative dynamic behaviours and permit mechanistic analysis of genotype-phenotype relationships.
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