z-logo
open-access-imgOpen Access
NucliTrack: an integrated nuclei tracking application
Author(s) -
Sam Cooper,
Alexis R. Barr,
Robert C. Glen,
Chris Bakal
Publication year - 2017
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btx404
Subject(s) - python (programming language) , computer science , source code , graphical user interface , toolbox , matlab , documentation , open source , tracking (education) , interface (matter) , computer graphics (images) , usability , mac os , software , programming language , human–computer interaction , operating system , psychology , pedagogy , bubble , maximum bubble pressure method
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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom