ArticleJournal of mathematical biology2016
A computational approach to persistence, permanence, and endotacticity of biochemical reaction systems.
Article in Journal of mathematical biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Advancing Mathematical Epidemiology and Chemical Reaction Network Theory via Synergies Between Them.Entropy (Basel, Switzerland) · 2024Article
- Conditions for extinction events in chemical reaction networks with discrete state spaces.Journal of mathematical biology · 2018Article
- Identifying parameter regions for multistationarity.PLoS computational biology · 2017Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We introduce a mixed-integer linear programming (MILP) framework capable of determining whether a chemical reaction network possesses the property of being endotactic or strongly endotactic. The network property of being strongly endotactic is known to lead to persistence and permanence of chemical species under genetic kinetic assumptions, while the same result is conjectured but as yet unproved for general endotactic networks. The algorithms we present are the first capable of verifying endotacticity of chemical reaction networks for systems with greater than two constituent species. We implement the algorithms in the open-source online package CoNtRol and apply them to a large sample of networks from the European Bioinformatics Institute's BioModels Database. We use strong endotacticity to establish for the first time the permanence of a well-studied circadian clock mechanism.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.