Format

Send to

Choose Destination
Bioinformatics. 2017 Oct 15;33(20):3320-3322. doi: 10.1093/bioinformatics/btx404.

NucliTrack: an integrated nuclei tracking application.

Author information

1
Division of Cancer Biology, The Institute of Cancer Research, London SW3 6JB, UK.
2
Department of Computational Systems Medicine, Imperial College, South Kensington Campus, London SW7 2AZ, UK.

Abstract

Summary:

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:

sam@socooper.com.

Supplementary information:

Supplementary data are available at Bioinformatics online.

PMID:
28637183
PMCID:
PMC5860035
DOI:
10.1093/bioinformatics/btx404
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Silverchair Information Systems Icon for PubMed Central
Loading ...
Support Center