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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 | 2014

The MIntAct project—IntAct as a common curation platform for 11 molecular interaction databases

Sandra Orchard; Mais G. Ammari; Bruno Aranda; L Breuza; Leonardo Briganti; Fiona Broackes-Carter; Nancy H. Campbell; Gayatri Chavali; Carol Chen; Noemi del-Toro; Margaret Duesbury; Marine Dumousseau; Eugenia Galeota; Ursula Hinz; Marta Iannuccelli; Sruthi Jagannathan; Rafael C. Jimenez; Jyoti Khadake; Astrid Lagreid; Luana Licata; Ruth C. Lovering; Birgit Meldal; Anna N. Melidoni; Mila Milagros; Daniele Peluso; Livia Perfetto; Pablo Porras; Arathi Raghunath; Sylvie Ricard-Blum; Bernd Roechert

IntAct (freely available at http://www.ebi.ac.uk/intact) is an open-source, open data molecular interaction database populated by data either curated from the literature or from direct data depositions. IntAct has developed a sophisticated web-based curation tool, capable of supporting both IMEx- and MIMIx-level curation. This tool is now utilized by multiple additional curation teams, all of whom annotate data directly into the IntAct database. Members of the IntAct team supply appropriate levels of training, perform quality control on entries and take responsibility for long-term data maintenance. Recently, the MINT and IntAct databases decided to merge their separate efforts to make optimal use of limited developer resources and maximize the curation output. All data manually curated by the MINT curators have been moved into the IntAct database at EMBL-EBI and are merged with the existing IntAct dataset. Both IntAct and MINT are active contributors to the IMEx consortium (http://www.imexconsortium.org).


BMC Biology | 2007

Broadening the horizon – level 2.5 of the HUPO-PSI format for molecular interactions

Samuel Kerrien; Sandra Orchard; Luisa Montecchi-Palazzi; Bruno Aranda; Antony F. Quinn; Nisha Vinod; Gary D. Bader; Ioannis Xenarios; Jérôme Wojcik; David James Sherman; Mike Tyers; John J. Salama; Susan Moore; Arnaud Ceol; Andrew Chatr-aryamontri; Matthias Oesterheld; Volker Stümpflen; Lukasz Salwinski; Jason Nerothin; Ethan Cerami; Michael E. Cusick; Marc Vidal; Michael K. Gilson; John Armstrong; Peter Woollard; Christopher W. V. Hogue; David Eisenberg; Gianni Cesareni; Rolf Apweiler; Henning Hermjakob

BackgroundMolecular interaction Information is a key resource in modern biomedical research. Publicly available data have previously been provided in a broad array of diverse formats, making access to this very difficult. The publication and wide implementation of the Human Proteome Organisation Proteomics Standards Initiative Molecular Interactions (HUPO PSI-MI) format in 2004 was a major step towards the establishment of a single, unified format by which molecular interactions should be presented, but focused purely on protein-protein interactions.ResultsThe HUPO-PSI has further developed the PSI-MI XML schema to enable the description of interactions between a wider range of molecular types, for example nucleic acids, chemical entities, and molecular complexes. Extensive details about each supported molecular interaction can now be captured, including the biological role of each molecule within that interaction, detailed description of interacting domains, and the kinetic parameters of the interaction. The format is supported by data management and analysis tools and has been adopted by major interaction data providers. Additionally, a simpler, tab-delimited format MITAB2.5 has been developed for the benefit of users who require only minimal information in an easy to access configuration.ConclusionThe PSI-MI XML2.5 and MITAB2.5 formats have been jointly developed by interaction data producers and providers from both the academic and commercial sector, and are already widely implemented and well supported by an active development community. PSI-MI XML2.5 enables the description of highly detailed molecular interaction data and facilitates data exchange between databases and users without loss of information. MITAB2.5 is a simpler format appropriate for fast Perl parsing or loading into Microsoft Excel.


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.


Nature Methods | 2011

PSICQUIC and PSISCORE: accessing and scoring molecular interactions

Bruno Aranda; Hagen Blankenburg; Samuel Kerrien; Fiona S. L. Brinkman; Arnaud Ceol; Emilie Chautard; Jose M. Dana; Javier De Las Rivas; Marine Dumousseau; Eugenia Galeota; Anna Gaulton; Johannes Goll; Robert E. W. Hancock; Ruth Isserlin; Rafael C. Jimenez; Jules Kerssemakers; Jyoti Khadake; David J. Lynn; Magali Michaut; Gavin O'Kelly; Keiichiro Ono; Sandra Orchard; Carlos Tejero Prieto; Sabry Razick; Olga Rigina; Lukasz Salwinski; Milan Simonovic; Sameer Velankar; Andrew Winter; Guanming Wu

To study proteins in the context of a cellular system, it is essential that the molecules with which a protein interacts are identified and the functional consequence of each interaction is understood. A plethora of resources now exist to capture molecular interaction data from the many laboratories generating…


Proteomics | 2009

The PSI semantic validator: a framework to check MIAPE compliance of proteomics data

Luisa Montecchi-Palazzi; Samuel Kerrien; Florian Reisinger; Bruno Aranda; Andrew R. Jones; Lennart Martens; Henning Hermjakob

The Human Proteome Organizations Proteomics Standards Initiative (PSI) promotes the development of exchange standards to improve data integration and interoperability. PSI specifies the suitable level of detail required when reporting a proteomics experiment (via the Minimum Information About a Proteomics Experiment), and provides extensible markup language (XML) exchange formats and dedicated controlled vocabularies (CVs) that must be combined to generate a standard compliant document. The framework presented here tackles the issue of checking that experimental data reported using a specific format, CVs and public bio‐ontologies (e.g. Gene Ontology, NCBI taxonomy) are compliant with the Minimum Information About a Proteomics Experiment recommendations. The semantic validator not only checks the XML syntax but it also enforces rules regarding the use of an ontology class or CV terms by checking that the terms exist in the resource and that they are used in the correct location of a document. Moreover, this framework is extremely fast, even on sizable data files, and flexible, as it can be adapted to any standard by customizing the parameters it requires: an XML Schema Definition, one or more CVs or ontologies, and a mapping file describing in a formal way how the semantic resources and the format are interrelated. As such, the validator provides a general solution to the common problem in data exchange: how to validate the correct usage of a data standard beyond simple XML Schema Definition validation. The framework source code and its various applications can be found at http://psidev.info/validator.


Genome Biology | 2008

MINT and IntAct contribute to the Second BioCreative challenge: serving the text-mining community with high quality molecular interaction data

Andrew Chatr-aryamontri; Samuel Kerrien; Jyoti Khadake; Sandra Orchard; Arnaud Ceol; Luana Licata; Luisa Castagnoli; Stefano Costa; Cathy Derow; Rachael P. Huntley; Bruno Aranda; Catherine Leroy; Dave Thorneycroft; Rolf Apweiler; Gianni Cesareni; Henning Hermjakob

BackgroundIn the absence of consolidated pipelines to archive biological data electronically, information dispersed in the literature must be captured by manual annotation. Unfortunately, manual annotation is time consuming and the coverage of published interaction data is therefore far from complete. The use of text-mining tools to identify relevant publications and to assist in the initial information extraction could help to improve the efficiency of the curation process and, as a consequence, the database coverage of data available in the literature. The 2006 BioCreative competition was aimed at evaluating text-mining procedures in comparison with manual annotation of protein-protein interactions.ResultsTo aid the BioCreative protein-protein interaction task, IntAct and MINT (Molecular INTeraction) provided both the training and the test datasets. Data from both databases are comparable because they were curated according to the same standards. During the manual curation process, the major cause of data loss in mining the articles for information was ambiguity in the mapping of the gene names to stable UniProtKB database identifiers. It was also observed that most of the information about interactions was contained only within the full-text of the publication; hence, text mining of protein-protein interaction data will require the analysis of the full-text of the articles and cannot be restricted to the abstract.ConclusionThe development of text-mining tools to extract protein-protein interaction information may increase the literature coverage achieved by manual curation. To support the text-mining community, databases will highlight those sentences within the articles that describe the interactions. These will supply data-miners with a high quality dataset for algorithm development. Furthermore, the dictionary of terms created by the BioCreative competitors could enrich the synonym list of the PSI-MI (Proteomics Standards Initiative-Molecular Interactions) controlled vocabulary, which is used by both databases to annotate their data content.


Current protocols in protein science | 2010

The Publication and Database Deposition of Molecular Interaction Data

Sandra Orchard; Bruno Aranda; Henning Hermjakob

Depositing data to a public domain interaction database not only improves the quality and quantity of interactions available to the user community, but also increases the visibility of the data, with members of the International Molecular Exchange (IMEx) databases making the information available in all participating resources. Datasets submitted prior to publication will be issued an accession number that may be included in a publication and which increases user accessibility to the data. No dataset is too small for submission, and the database curators will provide assistance in ensuring the information is correctly represented. This unit provides several alternative protocols to assist the author in preparing and submitting data as an integral part of the manuscript‐preparation process. Which method the author selects is largely dictated by the amount of data to be deposited. In addition, two support protocols describe assignment of unambiguous accession numbers and use of controlled vocabulary terms. Curr. Protoc. Protein Sci. 60:25.3.1‐25.3.13.


Journal of Proteome Research | 2012

Analyzing Protein–Protein Interaction Networks†

Gavin C. K. W. Koh; Pablo Porras; Bruno Aranda; Henning Hermjakob; Sandra Orchard

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Sandra Orchard

European Bioinformatics Institute

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Samuel Kerrien

European Bioinformatics Institute

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Henning Hermjakob

European Bioinformatics Institute

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Jyoti Khadake

University of British Columbia

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Marine Dumousseau

European Bioinformatics Institute

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Bernd Roechert

Swiss Institute of Bioinformatics

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Arathi Raghunath

University of British Columbia

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Carol Chen

University of British Columbia

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Alan Bridge

Swiss Institute of Bioinformatics

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