Control of cell state transitions.
Journal
Nature
ISSN: 1476-4687
Titre abrégé: Nature
Pays: England
ID NLM: 0410462
Informations de publication
Date de publication:
09 2022
09 2022
Historique:
received:
11
01
2021
accepted:
04
08
2022
pubmed:
15
9
2022
medline:
1
10
2022
entrez:
14
9
2022
Statut:
ppublish
Résumé
Understanding cell state transitions and purposefully controlling them is a longstanding challenge in biology. Here we present cell state transition assessment and regulation (cSTAR), an approach for mapping cell states, modelling transitions between them and predicting targeted interventions to convert cell fate decisions. cSTAR uses omics data as input, classifies cell states, and develops a workflow that transforms the input data into mechanistic models that identify a core signalling network, which controls cell fate transitions by influencing whole-cell networks. By integrating signalling and phenotypic data, cSTAR models how cells manoeuvre in Waddington's landscape
Identifiants
pubmed: 36104561
doi: 10.1038/s41586-022-05194-y
pii: 10.1038/s41586-022-05194-y
pmc: PMC9644236
mid: NIHMS1844164
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
975-985Subventions
Organisme : Medical Research Council
ID : MR/R015635/1
Pays : United Kingdom
Organisme : NCI NIH HHS
ID : R01 CA244660
Pays : United States
Informations de copyright
© 2022. The Author(s), under exclusive licence to Springer Nature Limited.
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