Mechanistic models of cell-fate transitions from single-cell data
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- dc.contributor.author Torregrosa, Gabriel
- dc.contributor.author García-Ojalvo, Jordi
- dc.date.accessioned 2022-03-17T10:05:26Z
- dc.date.available 2022-03-17T10:05:26Z
- dc.date.issued 2021
- dc.description.abstract Our knowledge of how individual cells self-organize to form complex multicellular systems is being revolutionized by a data outburst, coming from high-throughput experimental breakthroughs such as single-cell RNA sequencing and spatially resolved single-molecule FISH. This information is starting to be leveraged by machine-learning approaches that are helping us establish a census and timeline of cell types in developing organisms, shedding light on how biochemistry regulates cell-fate decisions. In parallel, imaging tools such as light-sheet microscopy are revealing how cells self-assemble in space and time as the organism forms, thereby elucidating the role of cell mechanics in development. Here we argue that mathematical modeling can bring together these two perspectives, by enabling us to test hypotheses about specific mechanisms, which can be further validated experimentally. We review the recent literature on this subject, focusing on representative examples that use modeling to better understand how single-cell behavior shapes multicellular organisms.
- dc.description.sponsorship This work was supported by the Spanish Ministry of Science, Innovation and Universities and FEDER (under projects PGC2018-101251-B-I00 and FIS2017-92551-EXP, and the ‘Maria de Maeztu’ Programme for Units of Excellence in R&D, grant CEX2018-000792-M), and by the Generalitat de Catalunya (ICREA Academia programme and grant 2017 SGR 1054). GT is funded by PhD grant FPU18/05091 from the Spanish Ministry of Science, Innovation and Universities
- dc.format.mimetype application/pdf
- dc.identifier.citation Torregrosa G, Garcia-Ojalvo J. Mechanistic models of cell-fate transitions from single-cell data. Curr Opin Syst Biol. 2021;26:79-86. DOI:10.1016/j.coisb.2021.04.004
- dc.identifier.doi http://dx.doi.org/10.1016/j.coisb.2021.04.004
- dc.identifier.issn 2452-3100
- dc.identifier.uri http://hdl.handle.net/10230/52708
- dc.language.iso eng
- dc.publisher Elsevier
- dc.rights © 2021. Gabriel Torregrosa and Jordi Garcia-Ojalvo. Mechanistic models of cell-fate transitions from single-cell data. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons. org/licenses/by/4.0/)
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri http://creativecommons.org/licenses/by/4.0/
- dc.subject.other Genètica
- dc.subject.other Embriologia
- dc.subject.other Bioquímica
- dc.title Mechanistic models of cell-fate transitions from single-cell data
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/publishedVersion