OmicsDI XML format
Created in 2017
How to cite this record FAIRsharing.org: OmicsDI XML format; OmicsDI XML format; DOI: https://doi.org/10.25504/FAIRsharing.2hqa97; Last edited: March 2, 2020, 12:25 p.m.; Last accessed: Jun 16 2021 9:28 a.m.
Record added: Oct. 5, 2017, 3:29 p.m.
Record updated: March 2, 2020, 12:25 p.m. by The FAIRsharing Team.
Edits to 'https://fairsharing.org/FAIRsharing.2hqa97' by 'The FAIRsharing Team' at 12:25, 02 Mar 2020 (not approved): 'miriam_id' has been modified: Before: After: None
Edits to 'https://fairsharing.org/FAIRsharing.2hqa97' by 'The FAIRsharing Team' at 10:18, 15 Mar 2018 (approved): 'miriam_url' has been modified: Before: None After:
|OmicsDI XML Validator||https://github.com/OmicsDI/xml-validator|
No XSD schemas defined
Conditions of UseApplies to: Data use
Discovering and linking public omics data sets using the Omics Discovery Index.
Perez-Riverol Y,Bai M,da Veiga Leprevost F,Squizzato S,Park YM,Haug K,Carroll AJ,Spalding D,Paschall J,Wang M,Del-Toro N,Ternent T,Zhang P,Buso N,Bandeira N,Deutsch EW,Campbell DS,Beavis RC,Salek RM,Sarkans U,Petryszak R,Keays M,Fahy E,Sud M,Subramaniam S,Barbera A,Jimenez RC,Nesvizhskii AI,Sansone SA,Steinbeck C,Lopez R,Vizcaino JA,Ping P,Hermjakob H
Nat Biotechnol 2017
No guidelines defined
No semantic standards defined
Models and Formats
No identifier schema standards defined
No metrics standards defined
The Expression Atlas is a free resource providing information on gene expression patterns under different biological conditions in a variety of species. Gene expression data is re-analysed in-house to detect genes showing interesting baseline and differential expression patterns, allowing a user to ask questions such as "what are the genes expressed in normal human liver" and "what genes are differentially expressed between water-stressed rice plants and controls with normal watering?" The resource features proteomics data sets provided by collaborators for corroboration between gene- and protein-level expression results. The latest component, Single Cell Expression Atlas, systematically reanalyses and visualises single cell RNA-sequencing datasets and helps answer questions such as what cell population a gene can act as a marker gene.
MetaboLights is a database for metabolomics studies, their raw experimental data and associated metadata. The database is cross-species and cross-technique and it covers metabolite structures and their reference spectra as well as their biological roles and locations. MetaboLights is the recommended metabolomics repository for a number of leading journals and ELIXIR, the European infrastructure for life science information.
ArrayExpress is a database of functional genomics experiments that can be queried and the data downloaded. It includes gene expression data from microarray and high throughput sequencing studies. Data is collected to MIAME and MINSEQE standards. Experiments are submitted directly to ArrayExpress or are imported from the NCBI GEO database.
BioModels is a repository of computational models of biological processes. It allows users to search and retrieve mathematical models published in the literature. Many models are manually curated (to ensure reproducibility) and extensively cross-linked to publicly available reference information.
PRoteomics IDEntifications database
The PRIDE PRoteomics IDEntifications database is a centralized, standards compliant, public data repository that provides protein and peptide identifications together with supporting evidence.
The European Genome-phenome Archive
The European Genome-phenome Archive (EGA) allows you to explore datasets from genomic studies, provided by a range of data providers. Access to datasets must be approved by the specified Data Access Committee (DAC).
The PeptideAtlas Project provides a publicly-accessible database of peptides identified in tandem mass spectrometry proteomics studies and software tools. Mass spectrometer output files are collected for human, mouse, yeast, and several other organisms, and sequence and spectral library searches are applied. Analyses are performed to produce a probability of correct identification for all results in a uniform manner, together with false discovery rates at the whole-atlas level.
The Global Proteome Machine Database
The Global Proteome Machine Database (gpmDB holds the minimum amount of information necessary for common bioinformatics-related tasks (such as sequence assignment validation) rather than being a complete record of a proteomics experiment. It was also created to aid in the process of validating peptide MS/MS spectra as well as protein coverage patterns. Most of the data is held in a set of XML files: the database serves as an index to those files, allowing for rapid lookups and reduced database storage requirements.
The Metabolomics Workbench serves as a national and international repository for metabolomics data and metadata and provides analysis tools and access to metabolite standards, protocols, tutorials, training, and more.
Library of Integrated Network-Based Cellular Signatures Data Portal
The LINCS Data Portal provides a unified interface for searching LINCS dataset packages and reagents. LINCS data are being made openly available as a community resource through a series of data releases, so as to enable scientists to address a broad range of basic research questions and to facilitate the identification of biological targets for new disease therapies. LINCS datasets consist of assay results from cultured and primary human cells treated with bioactive small molecules, ligands such as growth factors and cytokines, or genetic perturbations. Many different assays are used to monitor cell responses, including assays measuring transcript and protein expression; cell phenotype data are captured by biochemical and imaging readouts. Assays are typically carried out on multiple cell types, and at multiple timepoints; perturbagen activity is monitored at multiple doses.
Japan Proteome Standard Repository
jPOSTrepo (Japan ProteOme STandard Repository) is a data repository of sharing MS raw/processed data.
Omics Discovery Index
The Omics Discovery Index (OmicsDI) provides dataset discovery across a heterogeneous, distributed group of Transcriptomics, Genomics, Proteomics and Metabolomics data resources, including both open and controlled access data resources. The resource provides a short description of every dataset, including accession, description, sample/data protocols biological evidences, and publication. Based on these metadata, OmicsDI provides extensive search capabilities, as well as identification of related datasets by metadata and data content where possible. In particular, OmicsDI identifies groups of related, multi-omics datasets across repositories by shared identifiers.
Scroll for more...
This record is not implemented by any policy.
This record is in need of a maintainer. If you login, you'll be able to claim this record.
European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, UK (Research institute) Lead
National Center for Protein Sciences, Beijing, China (Research institute)