Decomposition classes and the structure and dynamics of reaction networks

Clicks: 1
ID: 286887
2021
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal

Ranked #3,580 of 3,757 articles by views in Malay Journal

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 3,757 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Many recent studies on Chemical Reaction Network Theory indicate that there is a renewed interest in network decomposition. These studies demonstrate the usefulness of decomposition in answering various problems about chemical reaction networks (CRNs). This thesis aims to contribute to this growing initiative by providing a study of important properties commonly shared by a CRN and its subnetworks. First, this study catalogues graph-theoretic properties (when a reaction network is viewed as a directed graph) and stoichiometric properties (when the reactions are considered as vectors in a Euclidean space) that can be lifted from the subnetworks to the parent network and vice versa. Second, the set of common complexes of subnetworks are associated with relevant properties including the so-called incidence-independence property, which has important implications on the capacity of a CRN to admit complex balanced equilibria. Finally, this study offers algorithms, based on existing theorems, that identify concentration robustness in CRNs by taking advantage of network decomposition. Overall, this thesis reiterates the relevance of decomposition of CRNs to study rich phenomena in networks by exposing interesting features of decomposition that were not considered in other studies.
Reference Key
persistent_1760659959_68f189f71778b Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Fontanil, Lauro L.
Journal Malay Journal
Year 2021
DOI
DOI not found
URL
https://animorepository.dlsu.edu.ph/etdd_math/1
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.