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      Community standards for open cell migration data


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          Cell migration research has become a high-content field. However, the quantitative information encapsulated in these complex and high-dimensional datasets is not fully exploited owing to the diversity of experimental protocols and non-standardized output formats. In addition, typically the datasets are not open for reuse. Making the data open and Findable, Accessible, Interoperable, and Reusable (FAIR) will enable meta-analysis, data integration, and data mining. Standardized data formats and controlled vocabularies are essential for building a suitable infrastructure for that purpose but are not available in the cell migration domain. We here present standardization efforts by the Cell Migration Standardisation Organisation (CMSO), an open community-driven organization to facilitate the development of standards for cell migration data. This work will foster the development of improved algorithms and tools and enable secondary analysis of public datasets, ultimately unlocking new knowledge of the complex biological process of cell migration.

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          Most cited references45

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          The minimum information about a genome sequence (MIGS) specification.

          With the quantity of genomic data increasing at an exponential rate, it is imperative that these data be captured electronically, in a standard format. Standardization activities must proceed within the auspices of open-access and international working bodies. To tackle the issues surrounding the development of better descriptions of genomic investigations, we have formed the Genomic Standards Consortium (GSC). Here, we introduce the minimum information about a genome sequence (MIGS) specification with the intent of promoting participation in its development and discussing the resources that will be required to develop improved mechanisms of metadata capture and exchange. As part of its wider goals, the GSC also supports improving the 'transparency' of the information contained in existing genomic databases.
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            Feature point tracking and trajectory analysis for video imaging in cell biology.

            This paper presents a computationally efficient, two-dimensional, feature point tracking algorithm for the automated detection and quantitative analysis of particle trajectories as recorded by video imaging in cell biology. The tracking process requires no a priori mathematical modeling of the motion, it is self-initializing, it discriminates spurious detections, and it can handle temporary occlusion as well as particle appearance and disappearance from the image region. The efficiency of the algorithm is validated on synthetic video data where it is compared to existing methods and its accuracy and precision are assessed for a wide range of signal-to-noise ratios. The algorithm is well suited for video imaging in cell biology relying on low-intensity fluorescence microscopy. Its applicability is demonstrated in three case studies involving transport of low-density lipoproteins in endosomes, motion of fluorescently labeled Adenovirus-2 particles along microtubules, and tracking of quantum dots on the plasma membrane of live cells. The present automated tracking process enables the quantification of dispersive processes in cell biology using techniques such as moment scaling spectra.
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              Metadata matters: access to image data in the real world

              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.

                Author and article information

                Oxford University Press
                12 May 2020
                May 2020
                12 May 2020
                : 9
                : 5
                : giaa041
                [1 ] Oxford e-Research Centre, Department of Engineering Science, University of Oxford , 7 Keble Road, Oxford OX1 3QG, Oxford, UK
                [3 ] VIB-UGent Center for Medical Biotechnology , VIB, A. Baertsoenkaai 3, B-9000, Ghent, Belgium
                [4 ] Department of Biomolecular Medicine, Ghent University , A. Baertsoenkaai 3, B-9000, Ghent, Belgium
                [5 ] Institute for Globally Distributed Open Research and Education (IGDORE) , Kabupaten Gianyar, Bali 80571, Indonesia
                [6 ] Department of Cell Biology, Radboud Institute for Molecular Life Sciences , Geert Grooteplein 28 6525 GA Nijmegen, The Netherlands
                [7 ] Centre for Gene Regulation & Expression & Division of Computational Biology, University of Dundee , School of Life Sciences, Dow St Dundee DD1 5EH, Scotland, UK
                [8 ] German Cancer Research Center, DKFZ Alumni Association , Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
                [9 ] David H. Koch Center for Applied Genitourinary Medicine, UT MD Anderson Cancer Center , 6767 Bertner Ave, Mitchell Basic Science Research Building, 77030 Houston, TX, USA
                [10 ] Cancer Genomics Center , Universiteitsweg 100, 3584 CG Utrecht, The Netherlands
                [11 ] Institute for Experimental Immunology and Imaging, University Hospital, University Duisburg-Essen , Universitätsstr. 2, 45141 Essen, Germany
                [12 ] Leibniz Institute for Analytical Sciences, ISAS , Bunsen-Kirchhoff-Straße 11, 44139 Dortmund, Germany
                [13 ] Department of Biophysics, UT Southwestern Medical Center , 5323 Harry Hines Blvd. Dallas, TX 75390, USA
                [14 ] Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University , 303 E. Chicago Ave, Chicago, IL 60611, USA
                [15 ] Division of Drug Discovery and Safety, Leiden Academic Centre for Drug Research , Leiden University, PO box 9502 2300 RA Leiden, The Netherlands
                [16 ] Center for Advanced Studies, Research, and Development in Sardinia (CRS4), Loc. Piscina Manna, Edificio 1, 09050 Pula (CA) , Italy
                [17 ] IDEA Bio-Medical Ltd , 2 Prof. Bergman St., Rehovot 76705, Israel
                [18 ] Life Science Core Facilities, Weizmann Institute of Science , P.O. Box 26 Rehovot 76100, Israel
                [19 ] Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, 5323 Harry Hines Blvd. Dallas, TX 75390 , USA
                [20 ] Department of Biosciences and Nutrition, Karolinska Institutet , Neo, SE-141 83 Huddinge, Sweden
                [21 ] Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev , P.O.B. 653, 8410501 Beer-Sheva, Israel
                Author notes
                Correspondence address. Susanna-Assunta Sansone, Oxford e-Research Centre, Department of Engineering Science, University of Oxford, Oxford e-Research Centre, 7 Keble Road, Oxford OX1 3QGOxford, UK. E-mail: susanna-assunta.sansone@ 123456oerc.ox.ac.uk
                Correspondence address. Lennart Martens, VIB and Ghent University, A. Baertsoenkaai 3, B-9000, Ghent, Belgium. E-mail: lennart.martens@ 123456vib-ugent.be

                Present address: Scientific Computing Department, Rutherford Appleton Laboratory, Science and Technology Facilities Council, Harwell Campus OX11 0QX, Didcot, UK

                Contributed equally to this work.

                Author information
                © The Author(s) 2020. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                : 26 October 2019
                : 02 April 2020
                : 02 April 2020
                Page count
                Pages: 11
                Funded by: Horizon 2020 Framework Programme, DOI 10.13039/100010661;
                Award ID: 634107
                Award ID: PHC32–2014

                cell migration,data standards,metadata,cmso,miacme,biotracks,frictionless data package,fair data


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