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Combining Model Reductions

Camporesi, Ferdinanda ; Feret, Jérôme ; Koeppl, Heinz ; Petrov, Tatjana (2024)
Combining Model Reductions.
In: Electronic Notes in Theoretical Computer Science, 2010, 265
doi: 10.26083/tuprints-00026719
Article, Secondary publication, Publisher's Version

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Item Type: Article
Type of entry: Secondary publication
Title: Combining Model Reductions
Language: English
Date: 30 April 2024
Place of Publication: Darmstadt
Year of primary publication: 2010
Place of primary publication: Amsterdam
Publisher: Elsevier
Journal or Publication Title: Electronic Notes in Theoretical Computer Science
Volume of the journal: 265
DOI: 10.26083/tuprints-00026719
Corresponding Links:
Origin: Secondary publication service

Molecular biological models usually suffer from a large combinatorial explosion. Indeed, proteins form complexes and modify each others, which leads to the formation of a huge number of distinct chemical species (i.e. non-isomorphic connected components of proteins). Thus we cannot generate explicitly the quantitative semantics of these models, and even less compute their properties. Model reduction aims at reducing this complexity by providing another grain of observation. In this paper, we propose two unifying frameworks for combining model reductions: we propose a symmetric product operator for combining model reductions for stochastic semantics and we show how to abstract further existing reduced differential systems by the means of linear projections. We apply both frameworks so as to abstract further existing reduced quantitative semantics of the models that are written in Kappa, by taking into account symmetries among binding sites in proteins.

Uncontrolled Keywords: rules-based modeling; model reduction; abstract interpretation; symmetries
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-267194
Classification DDC: 500 Science and mathematics > 570 Life sciences, biology
600 Technology, medicine, applied sciences > 621.3 Electrical engineering, electronics
Date Deposited: 30 Apr 2024 09:11
Last Modified: 30 Apr 2024 09:11
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/26719
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