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
 | There is a more recent version of this item available. |
Abstract
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.
| Item Type: | Article |
|---|---|
| Erschienen: | 2024 |
| Creators: | Camporesi, Ferdinanda ; Feret, Jérôme ; Koeppl, Heinz ; Petrov, Tatjana |
| 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 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/26719 |
| Corresponding Links: | |
| Origin: | Secondary publication service |
| Abstract: | 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: | 13 May 2024 09:54 |
| PPN: | |
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| Suche nach Titel in: | TUfind oder in Google |
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