Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Correlation-enhanced viable core in metabolic networks

Authors
Lee, Mi JinYi, SudoLee, Deok-Sun
Issue Date
May-2024
Publisher
Pergamon Press Ltd.
Keywords
Assortativity; Metabolic bipartite network; Viable core
Citation
Chaos, Solitons & Fractals, v.182, pp 1147761 - 1147767
Pages
7
Indexed
SCIE
SCOPUS
Journal Title
Chaos, Solitons & Fractals
Volume
182
Start Page
1147761
End Page
1147767
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/118467
DOI
10.1016/j.chaos.2024.114776
ISSN
0960-0779
1873-2887
Abstract
Cellular ingredient concentrations can be stabilized by adjusting generation and consumption rates through multiple pathways. To explore the portion of cellular metabolism equipped with multiple pathways, we categorize individual metabolic reactions and compounds as viable or inviable: A compound is viable if processed by two or more reactions, and a reaction is viable if all of its substrates and products are viable. Using this classification, we identify the maximal subnetwork of viable nodes, referred to as the viable core, in bipartite metabolic networks across thousands of species. The obtained viable cores are remarkably larger than those in degree-preserving randomized networks, while their broad degree distributions commonly enable the viable cores to shrink gradually as reaction nodes are deleted. We demonstrate by investigating the viable cores and the branching ratios of inviable nodes in the pruning process for artificial correlated networks that the positive degree–degree correlations of the empirical networks may underlie the enlarged viable cores compared to the randomized networks. By investigating the relation between degree and cross-species frequency of metabolic compounds and reactions, we elucidate the evolutionary origin of the correlations. Our study unveils the principle of metabolic resource allocation and its evolutionary mechanism, potentially useful for pharmaceutical applications. © 2024 Elsevier Ltd
Files in This Item
Appears in
Collections
COLLEGE OF SCIENCE AND CONVERGENCE TECHNOLOGY > DEPARTMENT OF APPLIED PHYSICS > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Lee, Mi Jin photo

Lee, Mi Jin
COLLEGE OF SCIENCE AND CONVERGENCE TECHNOLOGY (DEPARTMENT OF APPLIED PHYSICS)
Read more

Altmetrics

Total Views & Downloads

BROWSE