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Annual Scientific Report 2013 on the Cover Structure 3Fof in the Protein Data Bank, Determined by Laponogov, I
EMBL-European Bioinformatics Institute Annual Scientific Report 2013 On the cover Structure 3fof in the Protein Data Bank, determined by Laponogov, I. et al. (2009) Structural insight into the quinolone-DNA cleavage complex of type IIA topoisomerases. Nature Structural & Molecular Biology 16, 667-669. © 2014 European Molecular Biology Laboratory This publication was produced by the External Relations team at the European Bioinformatics Institute (EMBL-EBI) A digital version of the brochure can be found at www.ebi.ac.uk/about/brochures For more information about EMBL-EBI please contact: [email protected] Contents Introduction & overview 3 Services 8 Genes, genomes and variation 8 Molecular atlas 12 Proteins and protein families 14 Molecular and cellular structures 18 Chemical biology 20 Molecular systems 22 Cross-domain tools and resources 24 Research 26 Support 32 ELIXIR 36 Facts and figures 38 Funding & resource allocation 38 Growth of core resources 40 Collaborations 42 Our staff in 2013 44 Scientific advisory committees 46 Major database collaborations 50 Publications 52 Organisation of EMBL-EBI leadership 61 2013 EMBL-EBI Annual Scientific Report 1 Foreword Welcome to EMBL-EBI’s 2013 Annual Scientific Report. Here we look back on our major achievements during the year, reflecting on the delivery of our world-class services, research, training, industry collaboration and European coordination of life-science data. The past year has been one full of exciting changes, both scientifically and organisationally. We unveiled a new website that helps users explore our resources more seamlessly, saw the publication of ground-breaking work in data storage and synthetic biology, joined the global alliance for global health, built important new relationships with our partners in industry and celebrated the launch of ELIXIR. -
Impact of the Protein Data Bank Across Scientific Disciplines.Data Science Journal, 19: 25, Pp
Feng, Z, et al. 2020. Impact of the Protein Data Bank Across Scientific Disciplines. Data Science Journal, 19: 25, pp. 1–14. DOI: https://doi.org/10.5334/dsj-2020-025 RESEARCH PAPER Impact of the Protein Data Bank Across Scientific Disciplines Zukang Feng1,2, Natalie Verdiguel3, Luigi Di Costanzo1,4, David S. Goodsell1,5, John D. Westbrook1,2, Stephen K. Burley1,2,6,7,8 and Christine Zardecki1,2 1 Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ, US 2 Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ, US 3 University of Central Florida, Orlando, Florida, US 4 Department of Agricultural Sciences, University of Naples Federico II, Portici, IT 5 Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, US 6 Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA, US 7 Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ, US 8 Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, US Corresponding author: Christine Zardecki ([email protected]) The Protein Data Bank archive (PDB) was established in 1971 as the 1st open access digital data resource for biology and medicine. Today, the PDB contains >160,000 atomic-level, experimentally-determined 3D biomolecular structures. PDB data are freely and publicly available for download, without restrictions. Each entry contains summary information about the structure and experiment, atomic coordinates, and in most cases, a citation to a corresponding scien- tific publication. -
The HUPO Proteomics Standards Initiative Meeting: Towards Common Standards for Exchanging Proteomics Data Hinxton, Cambridge, UK, 19–20 October 2002
Comparative and Functional Genomics Comp Funct Genom 2003; 4: 16–19. Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/cfg.232 Feature Meeting Review: The HUPO Proteomics Standards Initiative meeting: towards common standards for exchanging proteomics data Hinxton, Cambridge, UK, 19–20 October 2002 Sandra Orchard, Paul Kersey, Henning Hermjakob* and Rolf Apweiler EMBL Outstation–European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK *Correspondence to: Abstract Henning Hermjakob, EMBL Outstation–European The Proteomics Standards Initiative (PSI) aims to define community standards Bioinformatics Institute, for data representation in proteomics and to facilitate data comparison, exchange Wellcome Trust Genome and verification. Initially the fields of protein–protein interactions (PPI) and mass Campus, Hinxton, Cambridge, spectroscopy have been targeted and the inaugural meeting of the PSI addressed the UK. questions of data storage and exchange in both of these areas. The PPI group rapidly E-mail: reached consensus as to the minimum requirements for a data exchange model; an [email protected] XML draft is now being produced. The mass spectroscopy group have achieved major advances in the definition of a required data model and working groups are currently taking these discussions further. A further meeting is planned in January 2003 to Received: 14 November 2002 advance both these projects. Copyright 2003 John Wiley & Sons, Ltd. Accepted: 14 November 2002 Keywords: proteomics; spectroscopy; protein–protein interactions Introduction process, before splitting into two working parties to address the issues facing their respective fields. The Proteomics Standards Initiative was estab- lished following a meeting in April 2002, jointly organized by HUPO and NAS, at which the urgent Protein–protein interactions (PPI) group need for standardization of proteomics data was recognized. -
The European Bioinformatics Institute in 2020: Building a Global Infrastructure of Interconnected Data Resources for the Life Sciences Charles E
Published online 8 November 2019 Nucleic Acids Research, 2020, Vol. 48, Database issue D17–D23 doi: 10.1093/nar/gkz1033 The European Bioinformatics Institute in 2020: building a global infrastructure of interconnected data resources for the life sciences Charles E. Cook *, Oana Stroe, Guy Cochrane ,EwanBirney and Rolf Apweiler European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK Received September 21, 2019; Revised October 18, 2019; Editorial Decision October 21, 2019; Accepted November 06, 2019 ABSTRACT ature. EMBL-EBI’s data resources collate, integrate, curate and make freely available to the public the world’s scientific Data resources at the European Bioinformatics In- data. stitute (EMBL-EBI, https://www.ebi.ac.uk/)archive, Our resources (www.ebi.ac.uk/services) include archival organize and provide added-value analysis of re- or deposition databases that store primary experimental search data produced around the world. This year’s data submitted by researchers, as well as knowledgebases update for EMBL-EBI focuses on data exchanges that integrate and add value to experimental data, with among resources, both within the institute and with many having both functions (1,2). All EMBL-EBI data re- a wider global infrastructure. Within EMBL-EBI, data sources, are open access and freely available to any user resources exchange data through a rich network of worldwide at any time, and EMBL-EBI strongly supports data flows mediated by automated systems. This net- the concept of FAIR data (findable, accessible, interopera- work ensures that users are served with as much ble, and resuable) (3). -
2003 Mulder Nucl Acids Res {22
The InterPro Database, 2003 brings increased coverage and new features Nicola J Mulder, Rolf Apweiler, Teresa K Attwood, Amos Bairoch, Daniel Barrell, Alex Bateman, David Binns, Margaret Biswas, Paul Bradley, Peer Bork, et al. To cite this version: Nicola J Mulder, Rolf Apweiler, Teresa K Attwood, Amos Bairoch, Daniel Barrell, et al.. The InterPro Database, 2003 brings increased coverage and new features. Nucleic Acids Research, Oxford University Press, 2003, 31 (1), pp.315-318. 10.1093/nar/gkg046. hal-01214149 HAL Id: hal-01214149 https://hal.archives-ouvertes.fr/hal-01214149 Submitted on 9 Oct 2015 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. # 2003 Oxford University Press Nucleic Acids Research, 2003, Vol. 31, No. 1 315–318 DOI: 10.1093/nar/gkg046 The InterPro Database, 2003 brings increased coverage and new features Nicola J. Mulder1,*, Rolf Apweiler1, Teresa K. Attwood3, Amos Bairoch4, Daniel Barrell1, Alex Bateman2, David Binns1, Margaret Biswas5, Paul Bradley1,3, Peer Bork6, Phillip Bucher7, Richard R. Copley8, Emmanuel Courcelle9, Ujjwal Das1, Richard Durbin2, Laurent Falquet7, Wolfgang Fleischmann1, Sam Griffiths-Jones2, Downloaded from Daniel Haft10, Nicola Harte1, Nicolas Hulo4, Daniel Kahn9, Alexander Kanapin1, Maria Krestyaninova1, Rodrigo Lopez1, Ivica Letunic6, David Lonsdale1, Ville Silventoinen1, Sandra E. -
MPGM: Scalable and Accurate Multiple Network Alignment
MPGM: Scalable and Accurate Multiple Network Alignment Ehsan Kazemi1 and Matthias Grossglauser2 1Yale Institute for Network Science, Yale University 2School of Computer and Communication Sciences, EPFL Abstract Protein-protein interaction (PPI) network alignment is a canonical operation to transfer biological knowledge among species. The alignment of PPI-networks has many applica- tions, such as the prediction of protein function, detection of conserved network motifs, and the reconstruction of species’ phylogenetic relationships. A good multiple-network align- ment (MNA), by considering the data related to several species, provides a deep understand- ing of biological networks and system-level cellular processes. With the massive amounts of available PPI data and the increasing number of known PPI networks, the problem of MNA is gaining more attention in the systems-biology studies. In this paper, we introduce a new scalable and accurate algorithm, called MPGM, for aligning multiple networks. The MPGM algorithm has two main steps: (i) SEEDGENERA- TION and (ii) MULTIPLEPERCOLATION. In the first step, to generate an initial set of seed tuples, the SEEDGENERATION algorithm uses only protein sequence similarities. In the second step, to align remaining unmatched nodes, the MULTIPLEPERCOLATION algorithm uses network structures and the seed tuples generated from the first step. We show that, with respect to different evaluation criteria, MPGM outperforms the other state-of-the-art algo- rithms. In addition, we guarantee the performance of MPGM under certain classes of net- work models. We introduce a sampling-based stochastic model for generating k correlated networks. We prove that for this model if a sufficient number of seed tuples are available, the MULTIPLEPERCOLATION algorithm correctly aligns almost all the nodes. -
Pdbefold Tutorial Tutorial Pdbefold Can May Be Accessed from Multiple Locations on the Pdbe Website
PDBe TUTORIAL PDBeFold (SSM: Secondary Structure Matching) http://pdbe.org/fold/ This PDBe tutorial introduces PDBeFold, an interactive service for comparing protein structures in 3D. This service provides: . Pairwise and multiple comparison and 3D alignment of protein structures . Examination of a protein structure for similarity with the whole Protein Data Bank (PDB) archive or SCOP. Best C -alignment of compared structures . Download and visualisation of best-superposed structures using various graphical packages PDBeFold structure alignment is based on identification of residues occupying “equivalent” geometrical positions. In other words, unlike sequence alignment, residue type is neglected. The PDBeFold service is a very powerful structure alignment tool which can perform both pairwise and multiple three dimensional alignment. In addition to this there are various options by which the results of the structural alignment query can be sorted. The results of the Secondary Structure Matching can be sorted based on the Q score (Cα- alignment), P score (taking into account RMSD, number of aligned residues, number of gaps, number of matched Secondary Structure Elements and the SSE match score), Z score (based on Gaussian Statistics), RMSD and % Sequence Identity. It is hoped that at the end of this tutorial users will be able to use PDbeFold for the analysis of their own uploaded structures or entries already in the PDB archive. Protein Data Bank in Europe http://pdbe.org PDBeFOLD Tutorial Tutorial PDBeFold can may be accessed from multiple locations on the PDBe website. From the PDBe home page (http://pdbe.org/), there are two access points for the program as shown below. -
Human Genetics 1990–2009
Portfolio Review Human Genetics 1990–2009 June 2010 Acknowledgements The Wellcome Trust would like to thank the many people who generously gave up their time to participate in this review. The project was led by Liz Allen, Michael Dunn and Claire Vaughan. Key input and support was provided by Dave Carr, Kevin Dolby, Audrey Duncanson, Katherine Littler, Suzi Morris, Annie Sanderson and Jo Scott (landscaping analysis), and Lois Reynolds and Tilli Tansey (Wellcome Trust Expert Group). We also would like to thank David Lynn for his ongoing support to the review. The views expressed in this report are those of the Wellcome Trust project team – drawing on the evidence compiled during the review. We are indebted to the independent Expert Group, who were pivotal in providing the assessments of the Wellcome Trust’s role in supporting human genetics and have informed ‘our’ speculations for the future. Finally, we would like to thank Professor Francis Collins, who provided valuable input to the development of the timelines. The Wellcome Trust is a charity registered in England and Wales, no. 210183. Contents Acknowledgements 2 Overview and key findings 4 Landmarks in human genetics 6 1. Introduction and background 8 2. Human genetics research: the global research landscape 9 2.1 Human genetics publication output: 1989–2008 10 3. Looking back: the Wellcome Trust and human genetics 14 3.1 Building research capacity and infrastructure 14 3.1.1 Wellcome Trust Sanger Institute (WTSI) 15 3.1.2 Wellcome Trust Centre for Human Genetics 15 3.1.3 Collaborations, consortia and partnerships 16 3.1.4 Research resources and data 16 3.2 Advancing knowledge and making discoveries 17 3.3 Advancing knowledge and making discoveries: within the field of human genetics 18 3.4 Advancing knowledge and making discoveries: beyond the field of human genetics – ‘ripple’ effects 19 Case studies 22 4. -
Annual Scientific Report 2011 Annual Scientific Report 2011 Designed and Produced by Pickeringhutchins Ltd
European Bioinformatics Institute EMBL-EBI Annual Scientific Report 2011 Annual Scientific Report 2011 Designed and Produced by PickeringHutchins Ltd www.pickeringhutchins.com EMBL member states: Austria, Croatia, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Israel, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom. Associate member state: Australia EMBL-EBI is a part of the European Molecular Biology Laboratory (EMBL) EMBL-EBI EMBL-EBI EMBL-EBI EMBL-European Bioinformatics Institute Wellcome Trust Genome Campus, Hinxton Cambridge CB10 1SD United Kingdom Tel. +44 (0)1223 494 444, Fax +44 (0)1223 494 468 www.ebi.ac.uk EMBL Heidelberg Meyerhofstraße 1 69117 Heidelberg Germany Tel. +49 (0)6221 3870, Fax +49 (0)6221 387 8306 www.embl.org [email protected] EMBL Grenoble 6, rue Jules Horowitz, BP181 38042 Grenoble, Cedex 9 France Tel. +33 (0)476 20 7269, Fax +33 (0)476 20 2199 EMBL Hamburg c/o DESY Notkestraße 85 22603 Hamburg Germany Tel. +49 (0)4089 902 110, Fax +49 (0)4089 902 149 EMBL Monterotondo Adriano Buzzati-Traverso Campus Via Ramarini, 32 00015 Monterotondo (Rome) Italy Tel. +39 (0)6900 91402, Fax +39 (0)6900 91406 © 2012 EMBL-European Bioinformatics Institute All texts written by EBI-EMBL Group and Team Leaders. This publication was produced by the EBI’s Outreach and Training Programme. Contents Introduction Foreword 2 Major Achievements 2011 4 Services Rolf Apweiler and Ewan Birney: Protein and nucleotide data 10 Guy Cochrane: The European Nucleotide Archive 14 Paul Flicek: -
Expert Review of Proteomics
Expert Review of Proteomics Editorial Advisory Panel Overseeing the editorial content and development of Expert Review of Proteomics is an Editorial Advisory Board, composed of many of the world's leading experts in the field, drawn from both research and academia. Albala JS, UC Davis School of Medicine, CA, USA Apweiler R, European Bioinformatics Institute, Cambridge, UK Dr Rolf Apweiler studied Biology with an emphasis on Molecular Biology and Biochemistry at the University of Heidelberg, Germany and the University of Bath, UK. He worked between 1991-1994 in drug discovery at Boehringer Mannheim and has been involved in the Swiss-Prot project since 1987. He co- ordinates the Swiss-Prot knowledgebase group at the EBI since 1994, and started the TrEMBL, InterPro, Proteome analysis and CluSTr projects at the EBI. Since autumn 2001 he is also in charge of the EMBL nucleotide sequence database and started in 2002 the merge of the Swiss-Prot and TrEMBL projects with the PIR to UniProt. Dr Apweiler is heading a team of currently 100 biologists and programmers responsible for the UniProt, InterPro, Proteome analysis, CluSTr and EMBL nucleotide sequence database projects at the EBI. Rolf Apweiler's main research interests are focused on integrating heterogenous functional genomic and proteomic data resources with the main protein and nucleotide sequence databases, and automation of classification and annotation of protein sequences. Blackburn J, Cambridge University, Cambridge, UK Professor Blackburn received a doctorate and an honours degree in chemistry from the University of Oxford. Following his Doctorate, Professor Blackburn carried out post-doctoral research with Professor Fersht at the Centre for Protein Engineering in Cambridge. -
EC-PSI: Associating Enzyme Commission Numbers with Pfam Domains
bioRxiv preprint doi: https://doi.org/10.1101/022343; this version posted July 10, 2015. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. EC-PSI: Associating Enzyme Commission Numbers with Pfam Domains Seyed Ziaeddin ALBORZI1;2, Marie-Dominique DEVIGNES3 and David W. RITCHIE2 1 Universite´ de Lorraine, LORIA, UMR 7503, Vandœuvre-les-Nancy,` F-54506, France 2 INRIA, Villers-les-Nancy,` F-54600, France 3 CNRS, LORIA, UMR 7503, Vandœuvre-les-Nancy,` F-54506, France Corresponding Author: [email protected] Abstract With the growing number of protein structures in the protein data bank (PDB), there is a need to annotate these structures at the domain level in order to relate protein structure to protein function. Thanks to the SIFTS database, many PDB chains are now cross-referenced with Pfam domains and enzyme commission (EC) numbers. However, these annotations do not include any explicit relationship between individual Pfam domains and EC numbers. This article presents a novel statistical training-based method called EC-PSI that can automatically infer high confi- dence associations between EC numbers and Pfam domains directly from EC-chain associations from SIFTS and from EC-sequence associations from the SwissProt, and TrEMBL databases. By collecting and integrating these existing EC-chain/sequence annotations, our approach is able to infer a total of 8,329 direct EC-Pfam associations with an overall F-measure of 0.819 with respect to the manually curated InterPro database, which we treat here as a “gold standard” reference dataset. -
RCSB Protein Data Bank: Overview
RCSB Protein Data Bank www.pdb.org RCSB Protein Data Bank: Overview Helen M. Berman July 24, 2009 Vision To provide a global resource for the advancement of research and education in biology and medicine by curating, integrating, and disseminating biological macromolecular structural information in the context of function, biological processes, evolution, pathways and disease states. We will implement standards, and anticipate and develop appropriate technologies to support evolving science. Structural Views of Biology and Medicine Mission Support a resource that is by, for, and of the community by providing . leadership in the representation of biological structures derived via experimental methods . data in an accurate and timely manner . comprehensive, integrated view and unique views of the data so as to enable scientific innovation and education What is the PDB? . Single international repository for all information about the structure of large biological molecules . Archival database with hundreds of thousands of users who depend on the data Archive Contents . Public archive . Internal archive – More than 400,000 files (as – Depositor correspondence of June, 2009) – Depositor contact information – Requires over 93 GBbytes of storage – Paper records – Data dictionaries – Documentation – Derived data files – Historical records from Day One . For each entry – Atomic coordinates – Sequence information – Description of structure – Experimental data – Release status information History of the PDB 1970s . Community discusses how to establish a protein structure archive . Cold Spring Harbor meeting in protein crystallography . PDB established at Brookhaven (Oct 1971; 7 structures) 1980s . Number of structures increases as technology improves . Community discussions about requiring depositions . IUCr guidelines established . Number of structures deposited increases 1990s .