Journal Article

DYNAMIK: a software environment for cell DYNAmics, Motility, and Information tracKing, with an application to Ras pathways

Stefan Jaeger, Qingfeng Song and Su-Shing Chen

in Bioinformatics

Volume 25, issue 18, pages 2383-2388
Published in print September 2009 | ISSN: 1367-4803
Published online July 2009 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btp405
DYNAMIK: a software environment for cell DYNAmics, Motility, and Information tracKing, with an application to Ras pathways

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The emergence of new microscopy techniques in combination with the increasing resource of bioimaging data has given fresh impetus to utilizing image processing methods for studying biological processes. Cell tracking studies in particular, which are important for a wide range of biological processes such as embryonic development or the immune system, have recently become the focus of attention. These studies typically produce large volumes of data that are hard to investigate manually and therefore call for an automated approach. Due to the large variety of biological cells and the inhomogeneity of applications, however, there exists no widely accepted method or system for cell tracking until today. In this article, we present our publicly available DYNAMIK software environment that allows users to compute a suit of cell features and plot the trajectory of multiple cells over a sequence of frames. Using chemotaxis and Ras pathways as an example, we show how users can employ our software to compute statistics about cell motility and other cell information, and how to evaluate their test series based on the data computed. We see that DYNAMIK's segmentation and tracking compares favorably with the output produced by other software packages.

Contact: jaeger@picb.ac.cn

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  4279 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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