The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Petri net modelling of biological networks
Open accessAbstract
Mathematical modelling is increasingly used to get insights into the functioning of complex biological networks. In this context, Petri nets (PNs) have recently emerged as a promising tool among the various methods employed for the modelling and analysis of molecular networks. PNs come with a series of extensions, which allow different abstraction levels, from purely qualitative to more complex quantitative models. Noteworthily, each of these models preserves the underlying graph, which depicts the interactions between the biological components. This article intends to present the basics of the approach and to foster the potential role PNs could play in the development of the computational systems biology.
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Cites
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Petri net theory and the modeling of systems
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Quantitative modeling of stochastic systems in molecular biology by using stochastic Petri nets
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A Guide to Conquer the Biological Network Era Using Graph Theory
Koutrouli, M., Karatzas, E., Paez-Espino, D., & Pavlopoulos, G. A. (2020) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2020.00034 · Cited by 264
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Zhao, S., Su, C., Lu, Z., & Wang, F. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa057 · Cited by 134
Synthesis of biological models from mutation experiments
Koksal, A. S., Pu, Y., Srivastava, S., Bodik, R., Fisher, J., & Piterman, N. (2013) · Proceedings of the 40th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages · doi:10.1145/2429069.2429125 · Cited by 36
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Metadata
- Authors
- Chaouiya, C.
- Venue
- Briefings in Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2007-03-29
- Volume
- 8
- Issue
- 4
- Pages
- 210-219
- ISSN
- 1467-5463 (ISSN-L)
- 1477-4054
- OpenAlex
- W2011835017
- Cited by
- 388
- References
- 36
- FWCI
- 9.70
- Type
- journal article
- Language
- en
- Open access
- bronze
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
