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Nucleic Acids Research | 2010

The IntAct molecular interaction database in 2010

Samuel Kerrien; Bruno Aranda; L Breuza; Alan Bridge; Fiona Broackes-Carter; Carol Chen; Margaret Duesbury; Marine Dumousseau; Marc Feuermann; Ursula Hinz; Christine Jandrasits; Rafael C. Jimenez; Jyoti Khadake; Usha Mahadevan; Patrick Masson; Ivo Pedruzzi; Eric Pfeiffenberger; Pablo Porras; Arathi Raghunath; Bernd Roechert; Sandra Orchard; Henning Hermjakob

IntAct is an open-source, open data molecular interaction database populated by data either curated from the literature or from direct data depositions. Two levels of curation are now available within the database, with both IMEx-level annotation and less detailed MIMIx-compatible entries currently supported. As from September 2011, IntAct contains approximately 275 000 curated binary interaction evidences from over 5000 publications. The IntAct website has been improved to enhance the search process and in particular the graphical display of the results. New data download formats are also available, which will facilitate the inclusion of IntActs data in the Semantic Web. IntAct is an active contributor to the IMEx consortium (http://www.imexconsortium.org). IntAct source code and data are freely available at http://www.ebi.ac.uk/intact.


Nucleic Acids Research | 2007

IntAct—open source resource for molecular interaction data

Samuel Kerrien; Yasmin Alam-Faruque; Bruno Aranda; I. Bancarz; Alan Bridge; C. Derow; Emily Dimmer; Marc Feuermann; A. Friedrichsen; Rachael P. Huntley; C. Kohler; Jyoti Khadake; Catherine Leroy; A. Liban; C. Lieftink; Luisa Montecchi-Palazzi; Sandra Orchard; Judith E. Risse; Karine Robbe; Bernd Roechert; David Thorneycroft; Y. Zhang; Rolf Apweiler; Henning Hermjakob

IntAct is an open source database and software suite for modeling, storing and analyzing molecular interaction data. The data available in the database originates entirely from published literature and is manually annotated by expert biologists to a high level of detail, including experimental methods, conditions and interacting domains. The database features over 126 000 binary interactions extracted from over 2100 scientific publications and makes extensive use of controlled vocabularies. The web site provides tools allowing users to search, visualize and download data from the repository. IntAct supports and encourages local installations as well as direct data submission and curation collaborations. IntAct source code and data are freely available from .


Nucleic Acids Research | 2012

New and continuing developments at PROSITE

Christian J. A. Sigrist; Edouard de Castro; Lorenzo Cerutti; Béatrice A. Cuche; Nicolas Hulo; Alan Bridge; Lydie Bougueleret; Ioannis Xenarios

PROSITE (http://prosite.expasy.org/) consists of documentation entries describing protein domains, families and functional sites, as well as associated patterns and profiles to identify them. It is complemented by ProRule a collection of rules, which increases the discriminatory power of these profiles and patterns by providing additional information about functionally and/or structurally critical amino acids. PROSITE signatures, together with ProRule, are used for the annotation of domains and features of UniProtKB/Swiss-Prot entries. Here, we describe recent developments that allow users to perform whole-proteome annotation as well as a number of filtering options that can be combined to perform powerful targeted searches for biological discovery. The latest version of PROSITE (release 20.85, of 30 August 2012) contains 1308 patterns, 1039 profiles and 1041 ProRules.


Nucleic Acids Research | 2017

InterPro in 2017—beyond protein family and domain annotations

Robert D. Finn; Teresa K. Attwood; Patricia C. Babbitt; Alex Bateman; Peer Bork; Alan Bridge; Hsin Yu Chang; Zsuzsanna Dosztányi; Sara El-Gebali; Matthew Fraser; Julian Gough; David R Haft; Gemma L. Holliday; Hongzhan Huang; Xiaosong Huang; Ivica Letunic; Rodrigo Lopez; Shennan Lu; Huaiyu Mi; Jaina Mistry; Darren A. Natale; Marco Necci; Gift Nuka; Christine A. Orengo; Youngmi Park; Sebastien Pesseat; Damiano Piovesan; Simon Potter; Neil D. Rawlings; Nicole Redaschi

InterPro (http://www.ebi.ac.uk/interpro/) is a freely available database used to classify protein sequences into families and to predict the presence of important domains and sites. InterProScan is the underlying software that allows both protein and nucleic acid sequences to be searched against InterPros predictive models, which are provided by its member databases. Here, we report recent developments with InterPro and its associated software, including the addition of two new databases (SFLD and CDD), and the functionality to include residue-level annotation and prediction of intrinsic disorder. These developments enrich the annotations provided by InterPro, increase the overall number of residues annotated and allow more specific functional inferences.


Nucleic Acids Research | 2012

The UniProt-GO Annotation database in 2011

Emily Dimmer; Rachael P. Huntley; Yasmin Alam-Faruque; Tony Sawford; Claire O'Donovan; María Martín; Benoit Bely; Paul Browne; Wei Mun Chan; Ruth Eberhardt; Michael Gardner; Kati Laiho; D Legge; Michele Magrane; Klemens Pichler; Diego Poggioli; Harminder Sehra; Andrea H. Auchincloss; Kristian B. Axelsen; Marie-Claude Blatter; Emmanuel Boutet; Silvia Braconi-Quintaje; Lionel Breuza; Alan Bridge; Elizabeth Coudert; Anne Estreicher; L Famiglietti; Serenella Ferro-Rojas; Marc Feuermann; Arnaud Gos

The GO annotation dataset provided by the UniProt Consortium (GOA: http://www.ebi.ac.uk/GOA) is a comprehensive set of evidenced-based associations between terms from the Gene Ontology resource and UniProtKB proteins. Currently supplying over 100 million annotations to 11 million proteins in more than 360 000 taxa, this resource has increased 2-fold over the last 2 years and has benefited from a wealth of checks to improve annotation correctness and consistency as well as now supplying a greater information content enabled by GO Consortium annotation format developments. Detailed, manual GO annotations obtained from the curation of peer-reviewed papers are directly contributed by all UniProt curators and supplemented with manual and electronic annotations from 36 model organism and domain-focused scientific resources. The inclusion of high-quality, automatic annotation predictions ensures the UniProt GO annotation dataset supplies functional information to a wide range of proteins, including those from poorly characterized, non-model organism species. UniProt GO annotations are freely available in a range of formats accessible by both file downloads and web-based views. In addition, the introduction of a new, normalized file format in 2010 has made for easier handling of the complete UniProt-GOA data set.


Nature Methods | 2012

Protein interaction data curation: the International Molecular Exchange (IMEx) consortium

Sandra Orchard; Samuel Kerrien; Sara Abbani; Bruno Aranda; Jignesh Bhate; Shelby Bidwell; Alan Bridge; Leonardo Briganti; Fiona S. L. Brinkman; Gianni Cesareni; Andrew Chatr-aryamontri; Emilie Chautard; Carol Chen; Marine Dumousseau; Johannes Goll; Robert E. W. Hancock; Linda I. Hannick; Igor Jurisica; Jyoti Khadake; David J. Lynn; Usha Mahadevan; Livia Perfetto; Arathi Raghunath; Sylvie Ricard-Blum; Bernd Roechert; Lukasz Salwinski; Volker Stümpflen; Mike Tyers; Peter Uetz; Ioannis Xenarios

The International Molecular Exchange (IMEx) consortium is an international collaboration between major public interaction data providers to share literature-curation efforts and make a nonredundant set of protein interactions available in a single search interface on a common website (http://www.imexconsortium.org/). Common curation rules have been developed, and a central registry is used to manage the selection of articles to enter into the dataset. We discuss the advantages of such a service to the user, our quality-control measures and our data-distribution practices.


Methods of Molecular Biology | 2016

UniProtKB/Swiss-Prot, the Manually Annotated Section of the UniProt KnowledgeBase: How to Use the Entry View

Emmanuel Boutet; Damien Lieberherr; Michael Tognolli; Michel Schneider; Parit Bansal; Alan Bridge; Sylvain Poux; Lydie Bougueleret; Ioannis Xenarios

The Universal Protein Resource (UniProt, http://www.uniprot.org ) consortium is an initiative of the SIB Swiss Institute of Bioinformatics (SIB), the European Bioinformatics Institute (EBI) and the Protein Information Resource (PIR) to provide the scientific community with a central resource for protein sequences and functional information. The UniProt consortium maintains the UniProt KnowledgeBase (UniProtKB), updated every 4 weeks, and several supplementary databases including the UniProt Reference Clusters (UniRef) and the UniProt Archive (UniParc).The Swiss-Prot section of the UniProt KnowledgeBase (UniProtKB/Swiss-Prot) contains publicly available expertly manually annotated protein sequences obtained from a broad spectrum of organisms. Plant protein entries are produced in the frame of the Plant Proteome Annotation Program (PPAP), with an emphasis on characterized proteins of Arabidopsis thaliana and Oryza sativa. High level annotations provided by UniProtKB/Swiss-Prot are widely used to predict annotation of newly available proteins through automatic pipelines.The purpose of this chapter is to present a guided tour of a UniProtKB/Swiss-Prot entry. We will also present some of the tools and databases that are linked to each entry.


Nucleic Acids Research | 2012

UniPathway: a resource for the exploration and annotation of metabolic pathways

Anne Morgat; Eric Coissac; Elisabeth Coudert; Kristian B. Axelsen; Guillaume Keller; Amos Marc Bairoch; Alan Bridge; Lydie Bougueleret; Ioannis Xenarios; Alain Viari

UniPathway (http://www.unipathway.org) is a fully manually curated resource for the representation and annotation of metabolic pathways. UniPathway provides explicit representations of enzyme-catalyzed and spontaneous chemical reactions, as well as a hierarchical representation of metabolic pathways. This hierarchy uses linear subpathways as the basic building block for the assembly of larger and more complex pathways, including species-specific pathway variants. All of the pathway data in UniPathway has been extensively cross-linked to existing pathway resources such as KEGG and MetaCyc, as well as sequence resources such as the UniProt KnowledgeBase (UniProtKB), for which UniPathway provides a controlled vocabulary for pathway annotation. We introduce here the basic concepts underlying the UniPathway resource, with the aim of allowing users to fully exploit the information provided by UniPathway.


Bioinformatics | 2012

Toward community standards in the quest for orthologs

Christophe Dessimoz; Toni Gabaldón; David S. Roos; Erik L. L. Sonnhammer; Javier Herrero; Adrian M. Altenhoff; Rolf Apweiler; Michael Ashburner; Judith A. Blake; Brigitte Boeckmann; Alan Bridge; Elspeth Bruford; Mike Cherry; Matthieu Conte; Durand Dannie; Ruchira S. Datta; Jean-Baka Domelevo Entfellner; Ingo Ebersberger; Michael Y. Galperin; Jacob M. Joseph; Tina Koestler; Evgenia V. Kriventseva; Odile Lecompte; Jack Leunissen; Suzanna E. Lewis; Benjamin Linard; Michael S. Livstone; Hui-Chun Lu; María Martín; Raja Mazumder

The identification of orthologs—genes pairs descended from a common ancestor through speciation, rather than duplication—has emerged as an essential component of many bioinformatics applications, ranging from the annotation of new genomes to experimental target prioritization. Yet, the development and application of orthology inference methods is hampered by the lack of consensus on source proteomes, file formats and benchmarks. The second ‘Quest for Orthologs’ meeting brought together stakeholders from various communities to address these challenges. We report on achievements and outcomes of this meeting, focusing on topics of particular relevance to the research community at large. The Quest for Orthologs consortium is an open community that welcomes contributions from all researchers interested in orthology research and applications. Contact: [email protected]


Nucleic Acids Research | 2013

HAMAP in 2013, new developments in the protein family classification and annotation system

Ivo Pedruzzi; Catherine Rivoire; Andrea H. Auchincloss; Elisabeth Coudert; Guillaume Keller; Edouard de Castro; Delphine Baratin; Béatrice A. Cuche; Lydie Bougueleret; Sylvain Poux; Nicole Redaschi; Ioannis Xenarios; Alan Bridge

HAMAP (High-quality Automated and Manual Annotation of Proteins—available at http://hamap.expasy.org/) is a system for the classification and annotation of protein sequences. It consists of a collection of manually curated family profiles for protein classification, and associated annotation rules that specify annotations that apply to family members. HAMAP was originally developed to support the manual curation of UniProtKB/Swiss-Prot records describing microbial proteins. Here we describe new developments in HAMAP, including the extension of HAMAP to eukaryotic proteins, the use of HAMAP in the automated annotation of UniProtKB/TrEMBL, providing high-quality annotation for millions of protein sequences, and the future integration of HAMAP into a unified system for UniProtKB annotation, UniRule. HAMAP is continuously updated by expert curators with new family profiles and annotation rules as new protein families are characterized. The collection of HAMAP family classification profiles and annotation rules can be browsed and viewed on the HAMAP website, which also provides an interface to scan user sequences against HAMAP profiles.

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Ioannis Xenarios

European Bioinformatics Institute

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Nicole Redaschi

Swiss Institute of Bioinformatics

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Sylvain Poux

Swiss Institute of Bioinformatics

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Elisabeth Coudert

Swiss Institute of Bioinformatics

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Anne Morgat

Swiss Institute of Bioinformatics

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Kristian B. Axelsen

Swiss Institute of Bioinformatics

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Edouard de Castro

Swiss Institute of Bioinformatics

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Marco Pagni

Swiss Institute of Bioinformatics

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Bruno Aranda

European Bioinformatics Institute

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