1. Data publication with the structural biology data grid supports live analysis
- Author
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Pa, Meyer, Socias S, Key J, Ransey E, Ec, Tjon, Alejandro Buschiazzo, Lei M, Botka C, Withrow J, Neau D, Rajashankar K, Ks, Anderson, Rh, Baxter, Sc, Blacklow, Tj, Boggon, Am, Bonvin, Borek D, Tj, Brett, Caflisch A, Ci, Chang, Department of Biological Chemistry and Molecular Pharmacology [Boston] (DBCMP), Harvard Medical School [Boston] (HMS), Molecular and structural microbiology = Microbiología Molecular y Estructural [Montevideo], Institut Pasteur de Montevideo, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), Shanghai Institutes for Biological Sciences (Institute of Biochemistry and Cell Biology), Chinese Academy of Sciences [Beijing] (CAS), NE-CAT and department of chemistry and chemical biology [Argonne], Cornell University, Departments of pharmacology and molecular biophysics and biochemistry [New Haven], Yale University School of Medicine, Department of Chemistry and Molecular Biophysics & Biochemistry [New Haven], Yale University [New Haven], Bijovet center [Utrecht], Utrecht University [Utrecht], Department of Biophysics and Biochemistry [Dallas], University of Texas Southwestern Medical Center [Dallas], Department of Internal Medicine [St Louis], Washington University School of Medicine, Department of Biochemistry [Zurich], University of Zürich [Zürich] (UZH), Institute of Biological Chemistry (IBC Sinica), Academia Sinica, Departments of biochemistry and chemistry [Nashville], Vanderbilt University [Nashville], Ludwig Institute for Cancer Research, University of California [San Diego] (UC San Diego), University of California, SUNY Upstate Medical University, State University of New York (SUNY), University of Chicago, Dana-Farber Cancer Institute [Boston], Saint Louis University School of Medicine [St Louis], Massachusetts Institute of Technology (MIT), Department of Biological Chemistry and Molecular Pharmacology (DBCMP), Columbia University [New York], National Heart, Lung, and Blood Institute [Bethesda] (NHLBI), Weill Institute for Cell and Molecular Biology, Howard Hughes Medical Institute [Stanford], Stanford University School of Medicine [CA, USA], Harvard University [Cambridge], Wuhan Institute of Virology, Howard Hughes Medical Institute [Boston], Tufts University School of Medicine [Boston], Queen's University [Kingston], La Trobe University [Melbourne], Geisel School of Medicine at Dartmouth, University of Cambridge [UK] (CAM), University of Texas at Dallas [Richardson] (UT Dallas), Campbell Family Institute for Breast Cancer Research, University Health Network, University of Toronto, Instituto de Biologia Molecular e Celular (IBMC), Institut de biologie structurale (IBS - UMR 5075), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche Interdisciplinaire de Grenoble (IRIG), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Grenoble Alpes (UGA), University of Maryland [Baltimore County] (UMBC), University of Maryland System, National Institute of Neurological Disorders and Stroke [Bethesda] (NINDS), National Institutes of Health [Bethesda] (NIH), Sealy Center for Structural Biology and Molecular Biophysics, The University of Texas Medical Branch (UTMB), Rice University [Houston], University of Washington School of Medicine, University of Kentucky, Boston Children's Hospital, Department of Computer Science, University of Chicago, University of California [San Francisco] (UCSF), Uppsala University, Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Howard Hughes Medical Institute [Ashburn], Fachbereich Biologie, University of Konstanz, Institute for Quantitative Social Sciences, Development of the Structural Biology Data Grid is funded by The Leona M. and Harry B. Helmsley Charitable Trust 2016PG-BRI002 to PS and MC. Development of citation workflows is supported NSF 1448069 (to PS). DAA is being developed as a pilot project of the National Data Service, with additional funds to support storage and technology development, including NIH P41 GM103403 (NE-CAT) and 1S10RR028832 (HMS) and DOE DE-AC02-06CH11357, NIH 1U54EB020406-01, Big Data for Discovery Science Center, and NIST 60NANB15D077 (Globus Project), Department of Biological Chemistry and Molecular Pharmacology [Boston] ( DBCMP ), Harvard Medical School [Boston] ( HMS ), Laboratory of molecular and structural microbiology, Institut Pasteur Montevideo-Réseau International des Instituts Pasteur ( RIIP ), Shanghai Institutes for Biological Sciences ( Institute of Biochemistry and Cell Biology ), Chinese Academy of Sciences [Beijing] ( CAS ), Yale University, Faculty of Science, Utrecht University, University of Zürich [Zürich] ( UZH ), Institute of Biological Chemistry ( IBC Sinica ), Vanderbilt University of Nashville, University of California [San Diego] ( UC San Diego ), Massachusetts Institute of Technology ( MIT ), Department of Biological Chemistry and Molecular Pharmacology ( DBCMP ), National Heart, Lung, and Blood Institute [Bethesda] ( NHLBI ), Stanford University School of Medicine, Havard Medical School, University of Cambridge [UK] ( CAM ), University of Texas at Dallas [Richardson] ( UT Dallas ), Instituto de Biologia Molecular e Celular ( IBMC ), Institut de biologie structurale ( IBS - UMR 5075 ), Université Joseph Fourier - Grenoble 1 ( UJF ) -Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ), University of Maryland Baltimore County [Baltimore] ( UMBC ), National Institute of Neurological Disorders and Stroke [Bethesda] ( NINDS ), National Institutes of Health [Bethesda] ( NIH ), The University of Texas Medical Branch ( UTMB ), Yale School of Medicine, University of California [San Francisco] ( UCSF ), Lawrence Berkeley National Laboratory [Berkeley] ( LBNL ), Massachusetts Institute of Technology. Department of Biology, Massachusetts Institute of Technology. Department of Chemistry, Drennan, Catherine L., Schwartz, Thomas, Institut de Recherche Interdisciplinaire de Grenoble (IRIG), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), and Instituto de Investigação e Inovação em Saúde
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Data set ,Data quality ,General Physics and Astronomy ,Experimental data ,General Chemistry ,Data grid ,General Biochemistry, Genetics and Molecular Biology ,Data science ,Genetics ,Paradigm shift ,Data access ,Data mining ,Biology ,The Internet - Abstract
The validation and analysis of X-ray crystallographic data is essential for reproducibility and the development of crystallographic methods. Here, the authors describe a repository for crystallographic datasets and demonstrate some of the ways it could serve the crystallographic community., Access to experimental X-ray diffraction image data is fundamental for validation and reproduction of macromolecular models and indispensable for development of structural biology processing methods. Here, we established a diffraction data publication and dissemination system, Structural Biology Data Grid (SBDG; data.sbgrid.org), to preserve primary experimental data sets that support scientific publications. Data sets are accessible to researchers through a community driven data grid, which facilitates global data access. Our analysis of a pilot collection of crystallographic data sets demonstrates that the information archived by SBDG is sufficient to reprocess data to statistics that meet or exceed the quality of the original published structures. SBDG has extended its services to the entire community and is used to develop support for other types of biomedical data sets. It is anticipated that access to the experimental data sets will enhance the paradigm shift in the community towards a much more dynamic body of continuously improving data analysis.
- Published
- 2016
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