RT Journal Article SR Electronic T1 Omics Discovery Index - Discovering and Linking Public ‘Omics’ Datasets JF bioRxiv FD Cold Spring Harbor Laboratory SP 049205 DO 10.1101/049205 A1 Yasset Perez-Riverol A1 Mingze Bai A1 Felipe da Veiga Leprevost A1 Silvano Squizzato A1 Young Mi Park A1 Kenneth Haug A1 Adam J. Carroll A1 Dylan Spalding A1 Justin Paschall A1 Mingxun Wang A1 Noemi del-Toro A1 Tobias Ternent A1 Peng Zhang A1 Nicola Buso A1 Nuno Bandeira A1 Eric W. Deutsch A1 David S Campbell A1 Ronald C. Beavis A1 Reza M. Salek A1 Alexey I. Nesvizhskii A1 Susanna-Assunta Sansone A1 Christoph Steinbeck A1 Rodrigo Lopez A1 Juan Antonio Vizcaíno A1 Peipei Ping A1 Henning Hermjakob YR 2016 UL http://biorxiv.org/content/early/2016/04/18/049205.abstract AB Biomedical data, in particular omics datasets are being generated at an unprecedented rate. This is due to the falling costs of generating experimental data, improved accuracy and better accessibility to different omics platforms such as genomics, proteomics and metabolomics1,2. As a result, the number of deposited datasets in public repositories originating from various omics approaches has increased dramatically in recent years. With strong support from scientific journals and funders, public data sharing is increasingly considered to be a good scientific practice, facilitating the confirmation of original results, increasing the reproducibility of the analyses, enabling the exploration of new or related hypotheses, and fostering the identification of potential errors, discouraging fraud3. This increase in public data deposition of omics results is a good starting point, but opens up a series of new challenges. For example the research community must now find more efficient ways for storing, organizing and providing access to biomedical data across platforms. These challenges range from achieving a common representation framework for the datasets and the associated metadata from different omics fields, to the availability of efficient methods, protocols and file formats for data exchange between multiple repositories. Therefore, there is a great need for development of new platforms and applications to make possible to search datasets across different omics fields, making such information accessible to the end-user. The FAIR paradigm describes a set of guiding principles to address many of these issues, and aims to make data Findable, Accessible, Interoperable and Re-usable(https://www.force11.org/group/fairgroup/fairprinciples).APIApplication Programming InterfacebioCADDIEbiomedical healthCAre Data Discovery and Index EcosystemCVControlled VocabularyDACData Access CommitteeDOIDigital Object IdentifierEGAEuropean Genome–Phenome ArchiveEuroPMCEurope PubMed CentralGNPSGlobal Natural Products Social Molecular NetworkingGPMDBGlobal Proteome Machine DatabaseMassIVEMass spectrometry Interactive Virtual EnvironmentPRIDEPRoteomics IDEntifications (PRIDE) databaseOmicsDIOmics Discovery IndexURLUniform Resource Identifier