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DC Field | Value | Language |
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dc.contributor.author | Liu, F | - |
dc.contributor.author | Sun, W | - |
dc.contributor.author | Heiner, M | - |
dc.contributor.author | Gilbert, D | - |
dc.date.accessioned | 2022-01-14T09:05:15Z | - |
dc.date.available | 2022-01-14T09:05:15Z | - |
dc.date.issued | 2019-12-15 | - |
dc.identifier | bbz114 | - |
dc.identifier.citation | Liu, F., Sun, W., Heiner, M. and Gilbert, D. (2021) 'Hybrid modelling of biological systems using fuzzy continuous Petri nets', Briefings in Bioinformatics, 22 (1), pp. 438 - 450, https://doi: 10.1093/bib/bbz114. | en_US |
dc.identifier.issn | 1467-5463 | - |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/23943 | - |
dc.description.abstract | Copyright © The Author(s) 2019. Integrated modelling of biological systems is challenged by composing components with sufficient kinetic data and components with insufficient kinetic data or components built only using experts’ experience and knowledge. Fuzzy continuous Petri nets (FCPNs) combine continuous Petri nets with fuzzy inference systems, and thus offer an hybrid uncertain/certain approach to integrated modelling of such biological systems with uncertainties. In this paper, we give a formal definition and a corresponding simulation algorithm of FCPNs, and briefly introduce the FCPN tool that we have developed for implementing FCPNs. We then present a methodology and workflow utilizing FCPNs to achieve hybrid (uncertain/certain) modelling of biological systems illustrated with a case study of the Mercaptopurine metabolic pathway. We hope this research will promote the wider application of FCPNs and address the uncertain/certain integrated modelling challenge in the systems biology area. | en_US |
dc.description.sponsorship | National Key R&D Program of China (2018YFC0830900); National Natural Science Foundation of China (61873094); Science and Technology Program of Guangzhou, China (201804010246); Natural Science Foundation of Guangdong Province of China (2018A030313338). | en_US |
dc.format.extent | 438 - 450 | - |
dc.language | English | - |
dc.language.iso | en_US | en_US |
dc.publisher | Oxford University Press (OUP) | en_US |
dc.rights | Copyright © The Author(s) 2019. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com | - |
dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0/ | - |
dc.subject | systems biology | en_US |
dc.subject | integrated modelling | en_US |
dc.subject | fuzzy continuous Petri nets | en_US |
dc.subject | uncertainties | en_US |
dc.subject | hybrid simulation | en_US |
dc.title | Hybrid modelling of biological systems using fuzzy continuous Petri nets | en_US |
dc.type | Article | en_US |
dc.identifier.doi | https://doi.org/10.1093/bib/bbz114 | - |
dc.relation.isPartOf | Briefings in Bioinformatics | - |
pubs.issue | 1 | - |
pubs.publication-status | Published | - |
pubs.volume | 22 | - |
dc.identifier.eissn | 1477-4054 | - |
Appears in Collections: | Dept of Computer Science Research Papers |
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