dc.contributor.author | Cooper, S | |
dc.contributor.author | Bakal, C | |
dc.date.accessioned | 2017-03-01T17:47:57Z | |
dc.date.issued | 2017-05-01 | |
dc.identifier.citation | Trends in biotechnology, 2017, 35 (5), pp. 422 - 433 | |
dc.identifier.issn | 0167-7799 | |
dc.identifier.uri | https://repository.icr.ac.uk/handle/internal/462 | |
dc.identifier.eissn | 1879-3096 | |
dc.identifier.doi | 10.1016/j.tibtech.2017.01.002 | |
dc.description.abstract | The dynamics of signalling networks that couple environmental conditions with cellular behaviour can now be characterised in exquisite detail using live single-cell imaging experiments. Recent improvements in our abilities to introduce fluorescent sensors into cells, coupled with advances in pipelines for quantifying and extracting single-cell data, mean that high-throughput systematic analyses of signalling dynamics are becoming possible. In this review, we consider current technologies that are driving progress in the scale and range of such studies. Moreover, we discuss novel approaches that are allowing us to explore how pathways respond to changes in inputs and even predict the fate of a cell based upon its signalling history and state. | |
dc.format | Print-Electronic | |
dc.format.extent | 422 - 433 | |
dc.language | eng | |
dc.language.iso | eng | |
dc.publisher | ELSEVIER SCIENCE LONDON | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0 | |
dc.subject | Cells, Cultured | |
dc.subject | Animals | |
dc.subject | Humans | |
dc.subject | Proteome | |
dc.subject | Gene Expression Profiling | |
dc.subject | Signal Transduction | |
dc.subject | Cell Physiological Phenomena | |
dc.subject | Molecular Imaging | |
dc.subject | Metabolic Engineering | |
dc.title | Accelerating Live Single-Cell Signalling Studies. | |
dc.type | Journal Article | |
dcterms.dateAccepted | 2017-01-06 | |
rioxxterms.versionofrecord | 10.1016/j.tibtech.2017.01.002 | |
rioxxterms.licenseref.uri | https://creativecommons.org/licenses/by/4.0 | |
rioxxterms.licenseref.startdate | 2017-05 | |
rioxxterms.type | Journal Article/Review | |
dc.relation.isPartOf | Trends in biotechnology | |
pubs.issue | 5 | |
pubs.notes | Not known | |
pubs.organisational-group | /ICR | |
pubs.organisational-group | /ICR/Primary Group | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Cancer Biology | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Cancer Biology/Dynamical Cell Systems | |
pubs.organisational-group | /ICR | |
pubs.organisational-group | /ICR/Primary Group | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Cancer Biology | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Cancer Biology/Dynamical Cell Systems | |
pubs.publication-status | Published | |
pubs.volume | 35 | |
pubs.embargo.terms | Not known | |
icr.researchteam | Dynamical Cell Systems | |
dc.contributor.icrauthor | Bakal, Christopher | |