Chemical reaction network properties of S-systems and decompositions of reaction networks

Clicks: 3
ID: 286886
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
Emerging

Ranked #3,321 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
This thesis examined two models of the gene regulatory system of Mycobacterium Tuberculosis (Mtb) presented as S-system by Magombedze and Mulder (2013). The models are partitioned into three subsystems based on putative gene function and role in dormancy/latency development. This study investigated the chemical reaction network (CRN) representation of the Mtb models and each subsystem to obtain new mathematical results in Chemical Reaction Network Theory. The subsystems are represented as embedded networks (an arc connecting two vertices that represent genes from different subsystems is retained). For the embedded networks of S_system CRNs (with at least two species) are discordant. Analyzing the subsystems as subnetworks, we formed a digraph homomorphism from the corresponding subnetworks to the embedded networks and explored the modularity concepts of digraph. Further analysis of the Mtb S-systems led us to develop different classes of decomposition of reaction networks based on the approach of Feinberg (1987) in decomposing a CRN and were used to correct a deficiency formula of Arceo et al. (2015).
Reference Key
persistent_1760659956_68f189f48bb66 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Farinas, Honeylou F.
Journal Malay Journal
Year 2021
DOI
DOI not found
URL
https://animorepository.dlsu.edu.ph/etdd_math/3
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.