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dc.contributor.authorCooper, S
dc.contributor.authorBarr, AR
dc.contributor.authorGlen, R
dc.contributor.authorBakal, C
dc.date.accessioned2017-09-04T10:54:43Z
dc.date.issued2017-10-15
dc.identifier.citationBioinformatics (Oxford, England), 2017, 33 (20), pp. 3320 - 3322
dc.identifier.issn1367-4803
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/809
dc.identifier.eissn1367-4811
dc.identifier.doi10.1093/bioinformatics/btx404
dc.description.abstractSUMMARY: Live imaging studies give unparalleled insight into dynamic single cell behaviours and fate decisions. However, the challenge of reliably tracking single cells over long periods of time limits both the throughput and ease with which such studies can be performed. Here, we present NucliTrack, a cross platform solution for automatically segmenting, tracking and extracting features from fluorescently labelled nuclei. NucliTrack performs similarly to other state-of-the-art cell tracking algorithms, but NucliTrack's interactive, graphical interface makes it significantly more user friendly. AVAILABILITY AND IMPLEMENTATION: NucliTrack is available as a free, cross platform application and open source Python package. Installation details and documentation are at: http://nuclitrack.readthedocs.io/en/latest/ A video guide can be viewed online: https://www.youtube.com/watch?v=J6e0D9F-qSU Source code is available through Github: https://github.com/samocooper/nuclitrack. A Matlab toolbox is also available at: https://uk.mathworks.com/matlabcentral/fileexchange/61479-samocooper-nuclitrack-matlab. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
dc.formatPrint
dc.format.extent3320 - 3322
dc.languageeng
dc.language.isoeng
dc.publisherOXFORD UNIV PRESS
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.subjectCell Nucleus
dc.subjectAlgorithms
dc.subjectImage Processing, Computer-Assisted
dc.subjectSoftware
dc.subjectCell Tracking
dc.titleNucliTrack: an integrated nuclei tracking application.
dc.typeJournal Article
dcterms.dateAccepted2017-06-17
rioxxterms.versionofrecord10.1093/bioinformatics/btx404
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0
rioxxterms.licenseref.startdate2017-10
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfBioinformatics (Oxford, England)
pubs.issue20
pubs.notesNot 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-statusPublished
pubs.volume33
pubs.embargo.termsNot known
icr.researchteamDynamical Cell Systems
dc.contributor.icrauthorBarr, Alexis
dc.contributor.icrauthorBakal, Christopher


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