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      Metadata matters: access to image data in the real world

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          Abstract

          Data sharing is important in the biological sciences to prevent duplication of effort, to promote scientific integrity, and to facilitate and disseminate scientific discovery. Sharing requires centralized repositories, and submission to and utility of these resources require common data formats. This is particularly challenging for multidimensional microscopy image data, which are acquired from a variety of platforms with a myriad of proprietary file formats (PFFs). In this paper, we describe an open standard format that we have developed for microscopy image data. We call on the community to use open image data standards and to insist that all imaging platforms support these file formats. This will build the foundation for an open image data repository.

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          Most cited references17

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          Phenotypic profiling of the human genome by time-lapse microscopy reveals cell division genes.

          Despite our rapidly growing knowledge about the human genome, we do not know all of the genes required for some of the most basic functions of life. To start to fill this gap we developed a high-throughput phenotypic screening platform combining potent gene silencing by RNA interference, time-lapse microscopy and computational image processing. We carried out a genome-wide phenotypic profiling of each of the approximately 21,000 human protein-coding genes by two-day live imaging of fluorescently labelled chromosomes. Phenotypes were scored quantitatively by computational image processing, which allowed us to identify hundreds of human genes involved in diverse biological functions including cell division, migration and survival. As part of the Mitocheck consortium, this study provides an in-depth analysis of cell division phenotypes and makes the entire high-content data set available as a resource to the community.
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            Global analysis of mRNA localization reveals a prominent role in organizing cellular architecture and function.

            Although subcellular mRNA trafficking has been demonstrated as a mechanism to control protein distribution, it is generally believed that most protein localization occurs subsequent to translation. To address this point, we developed and employed a high-resolution fluorescent in situ hybridization procedure to comprehensively evaluate mRNA localization dynamics during early Drosophila embryogenesis. Surprisingly, of the 3370 genes analyzed, 71% of those expressed encode subcellularly localized mRNAs. Dozens of new and striking localization patterns were observed, implying an equivalent variety of localization mechanisms. Tight correlations between mRNA distribution and subsequent protein localization and function, indicate major roles for mRNA localization in nucleating localized cellular machineries. A searchable web resource documenting mRNA expression and localization dynamics has been established and will serve as an invaluable tool for dissecting localization mechanisms and for predicting gene functions and interactions.
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              Full-genome RNAi profiling of early embryogenesis in Caenorhabditis elegans.

              A key challenge of functional genomics today is to generate well-annotated data sets that can be interpreted across different platforms and technologies. Large-scale functional genomics data often fail to connect to standard experimental approaches of gene characterization in individual laboratories. Furthermore, a lack of universal annotation standards for phenotypic data sets makes it difficult to compare different screening approaches. Here we address this problem in a screen designed to identify all genes required for the first two rounds of cell division in the Caenorhabditis elegans embryo. We used RNA-mediated interference to target 98% of all genes predicted in the C. elegans genome in combination with differential interference contrast time-lapse microscopy. Through systematic annotation of the resulting movies, we developed a phenotypic profiling system, which shows high correlation with cellular processes and biochemical pathways, thus enabling us to predict new functions for previously uncharacterized genes.
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                Author and article information

                Journal
                J Cell Biol
                J. Cell Biol
                jcb
                The Journal of Cell Biology
                The Rockefeller University Press
                0021-9525
                1540-8140
                31 May 2010
                : 189
                : 5
                : 777-782
                Affiliations
                [1 ]Laboratory for Optical and Computational Instrumentation, Department of Molecular Biology and [2 ]Department of Biomedical Engineering, Graduate School, University of Wisconsin at Madison, Madison, WI 53711
                [3 ]Wellcome Trust Centre for Gene Regulation and Expression, College of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland, UK
                [4 ]Glencoe Software, Inc., Seattle, WA 98101
                [5 ]The Rockefeller University Press, New York, NY 10065
                Author notes
                Correspondence to Kevin W. Eliceiri: eliceiri@ 123456wisc.edu ; or Jason R. Swedlow: jason@ 123456lifesci.dundee.ac.uk
                Article
                201004104
                10.1083/jcb.201004104
                2878938
                20513764
                39d034ac-8621-4eee-9e98-0f757a208831
                © 2010 Linkert et al.

                This article is distributed under the terms of an Attribution–Noncommercial–Share Alike–No Mirror Sites license for the first six months after the publication date (see http://www.rupress.org/terms). After six months it is available under a Creative Commons License (Attribution–Noncommercial–Share Alike 3.0 Unported license, as described at http://creativecommons.org/licenses/by-nc-sa/3.0/).

                History
                : 21 April 2010
                : 5 May 2010
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                Cell biology
                Cell biology

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