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An image analysis toolbox for high-throughput C. elegans assays
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab.
Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA.
Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA.
(Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA)
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2012 (English)In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 9, no 7, 714-716 p.Article in journal (Refereed) Published
Abstract [en]

We present a toolbox for high-throughput screening of image-based Caenorhabditis elegans phenotypes. The image analysis algorithms measure morphological phenotypes in individual worms and are effective for a variety of assays and imaging systems from different laboratories. The toolbox is available via the open-source CellProfiler project and enables objective scoring of whole-animal high-throughput image-based assays using this unique model organism for the study of diverse biological pathways relevant to human disease.

Place, publisher, year, edition, pages
2012. Vol. 9, no 7, 714-716 p.
Keyword [en]
C. elegans, image analysis, image based screening
National Category
Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
URN: urn:nbn:se:uu:diva-175224DOI: 10.1038/nmeth.1984ISI: 000305942200026PubMedID: 22522656OAI: oai:DiVA.org:uu-175224DiVA: diva2:530598
Available from: 2012-06-04 Created: 2012-06-04 Last updated: 2017-12-07Bibliographically approved

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Wählby, Carolina

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