Scalable reaction network modeling with automatic validation of consistency in Event-B
Scalable reaction network modeling with automatic validation of consistency in Event-B
Constructing a large biological model is a difficult, error-prone process. Small errors in writing a part of the model cascade to the system level and their sources are difficult to trace back. In this paper we extend a recent approach based on Event-B, a state-based formal method with refinement as its central ingredient, allowing us to validate for model consistency step-by-step in an automated way. We demonstrate this approach on a model of the heat shock response in eukaryotes and its scalability on a model of the ErbB signaling pathway. All consistency properties of the model were proved automatically with computer support.
1287
Sanwal, Usman
3651c8cf-23fe-4d75-8f89-db1fcbcacf88
Hoang, Thai Son
dcc0431d-2847-4e1d-9a85-54e4d6bab43f
Petre, Luigia
2a81e9f4-b9fd-4537-9e90-ff0d07562153
Petre, Ion
d942b378-d1e6-497c-b543-31366e9aeb2d
25 January 2022
Sanwal, Usman
3651c8cf-23fe-4d75-8f89-db1fcbcacf88
Hoang, Thai Son
dcc0431d-2847-4e1d-9a85-54e4d6bab43f
Petre, Luigia
2a81e9f4-b9fd-4537-9e90-ff0d07562153
Petre, Ion
d942b378-d1e6-497c-b543-31366e9aeb2d
Sanwal, Usman, Hoang, Thai Son, Petre, Luigia and Petre, Ion
(2022)
Scalable reaction network modeling with automatic validation of consistency in Event-B.
Scientific Reports, 12 (1), , [1287].
(doi:10.1038/s41598-022-05308-6).
Abstract
Constructing a large biological model is a difficult, error-prone process. Small errors in writing a part of the model cascade to the system level and their sources are difficult to trace back. In this paper we extend a recent approach based on Event-B, a state-based formal method with refinement as its central ingredient, allowing us to validate for model consistency step-by-step in an automated way. We demonstrate this approach on a model of the heat shock response in eukaryotes and its scalability on a model of the ErbB signaling pathway. All consistency properties of the model were proved automatically with computer support.
Text
s41598-022-05308-6
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Accepted/In Press date: 8 December 2021
Published date: 25 January 2022
Additional Information:
© 2022. The Author(s).
Identifiers
Local EPrints ID: 457533
URI: http://eprints.soton.ac.uk/id/eprint/457533
ISSN: 2045-2322
PURE UUID: 5ba90dbf-3b07-46dc-9810-12ac29d40e2a
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Date deposited: 10 Jun 2022 16:37
Last modified: 18 Mar 2024 03:32
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Author:
Usman Sanwal
Author:
Thai Son Hoang
Author:
Luigia Petre
Author:
Ion Petre
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