Phenotype-specific estimation of metabolic fluxes using gene expression data.
Cellular physiology
Complex system biology
Omics
Transcriptomics
Journal
iScience
ISSN: 2589-0042
Titre abrégé: iScience
Pays: United States
ID NLM: 101724038
Informations de publication
Date de publication:
17 Mar 2023
17 Mar 2023
Historique:
received:
22
09
2022
revised:
30
11
2022
accepted:
10
02
2023
entrez:
14
3
2023
pubmed:
15
3
2023
medline:
15
3
2023
Statut:
epublish
Résumé
A cell's genome influences its metabolism via the expression of enzyme-related genes, but transcriptome and fluxome are not perfectly correlated as post-transcriptional mechanisms also regulate reaction's kinetics. Here, we addressed the question: given a transcriptome, how unobserved mechanisms of reaction kinetics should be systematically accounted for when inferring the fluxome? To infer the most likely and least biased fluxome, we present Pheflux, a constraint-based model maximizing Shannon's entropy of fluxes per mRNA. Benchmarked against
Identifiants
pubmed: 36915687
doi: 10.1016/j.isci.2023.106201
pii: S2589-0042(23)00278-X
pmc: PMC10006673
doi:
Types de publication
Journal Article
Langues
eng
Pagination
106201Informations de copyright
© 2023 The Author(s).
Déclaration de conflit d'intérêts
The authors declare no competing interest.
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