Scalable reaction network modeling with automatic validation of consistency in Event-B.
Sci Rep 2022;
12:1287. [PMID:
35079072 PMCID:
PMC8789811 DOI:
10.1038/s41598-022-05308-6]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 12/08/2021] [Indexed: 11/27/2022] Open
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 \documentclass[12pt]{minimal}
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\begin{document}$$\mathsf {ErbB}$$\end{document}ErbB signaling pathway. All consistency properties of the model were proved automatically with computer support.
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