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1.
Nucleic Acids Res ; 50(D1): D648-D653, 2022 01 07.
Article in English | MEDLINE | ID: mdl-34761267

ABSTRACT

The IntAct molecular interaction database (https://www.ebi.ac.uk/intact) is a curated resource of molecular interactions, derived from the scientific literature and from direct data depositions. As of August 2021, IntAct provides more than one million binary interactions, curated by twelve global partners of the International Molecular Exchange consortium, for which the IntAct database provides a shared curation and dissemination platform. The IMEx curation policy has always emphasised a fine-grained data and curation model, aiming to capture the relevant experimental detail essential for the interpretation of the provided molecular interaction data. Here, we present recent curation focus and progress, as well as a completely redeveloped website which presents IntAct data in a much more user-friendly and detailed way.


Subject(s)
Databases, Protein , Protein Interaction Maps/genetics , Software , Humans , Protein Interaction Mapping/methods
2.
Nat Commun ; 11(1): 6144, 2020 12 01.
Article in English | MEDLINE | ID: mdl-33262342

ABSTRACT

The International Molecular Exchange (IMEx) Consortium provides scientists with a single body of experimentally verified protein interactions curated in rich contextual detail to an internationally agreed standard. In this update to the work of the IMEx Consortium, we discuss how this initiative has been working in practice, how it has ensured database sustainability, and how it is meeting emerging annotation challenges through the introduction of new interactor types and data formats. Additionally, we provide examples of how IMEx data are being used by biomedical researchers and integrated in other bioinformatic tools and resources.


Subject(s)
Access to Information , Databases, Genetic , Humans , Information Dissemination , International Cooperation
3.
Nat Commun ; 11(1): 3400, 2020 07 07.
Article in English | MEDLINE | ID: mdl-32636365

ABSTRACT

The Pan-Cancer Analysis of Whole Genomes (PCAWG) project generated a vast amount of whole-genome cancer sequencing resource data. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we provide a user's guide to the five publicly available online data exploration and visualization tools introduced in the PCAWG marker paper. These tools are ICGC Data Portal, UCSC Xena, Chromothripsis Explorer, Expression Atlas, and PCAWG-Scout. We detail use cases and analyses for each tool, show how they incorporate outside resources from the larger genomics ecosystem, and demonstrate how the tools can be used together to understand the biology of cancers more deeply. Together, the tools enable researchers to query the complex genomic PCAWG data dynamically and integrate external information, enabling and enhancing interpretation.


Subject(s)
Computational Biology/methods , Genome, Human , Neoplasms/genetics , Chromothripsis , Data Analysis , Databases, Genetic , Genomics , Humans , Internet , Mutation , Software , User-Computer Interface , Whole Genome Sequencing
4.
Nucleic Acids Res ; 46(D1): D246-D251, 2018 01 04.
Article in English | MEDLINE | ID: mdl-29165655

ABSTRACT

Expression Atlas (http://www.ebi.ac.uk/gxa) is an added value database that provides information about gene and protein expression in different species and contexts, such as tissue, developmental stage, disease or cell type. The available public and controlled access data sets from different sources are curated and re-analysed using standardized, open source pipelines and made available for queries, download and visualization. As of August 2017, Expression Atlas holds data from 3,126 studies across 33 different species, including 731 from plants. Data from large-scale RNA sequencing studies including Blueprint, PCAWG, ENCODE, GTEx and HipSci can be visualized next to each other. In Expression Atlas, users can query genes or gene-sets of interest and explore their expression across or within species, tissues, developmental stages in a constitutive or differential context, representing the effects of diseases, conditions or experimental interventions. All processed data matrices are available for direct download in tab-delimited format or as R-data. In addition to the web interface, data sets can now be searched and downloaded through the Expression Atlas R package. Novel features and visualizations include the on-the-fly analysis of gene set overlaps and the option to view gene co-expression in experiments investigating constitutive gene expression across tissues or other conditions.


Subject(s)
Databases, Genetic , Animals , Gene Expression Profiling , Humans , Mammals/genetics , Mammals/metabolism , Oligonucleotide Array Sequence Analysis , Plants/genetics , Plants/metabolism , Proteomics , Sequence Analysis, RNA , Species Specificity , User-Computer Interface
5.
Nucleic Acids Res ; 44(D1): D746-52, 2016 Jan 04.
Article in English | MEDLINE | ID: mdl-26481351

ABSTRACT

Expression Atlas (http://www.ebi.ac.uk/gxa) provides information about gene and protein expression in animal and plant samples of different cell types, organism parts, developmental stages, diseases and other conditions. It consists of selected microarray and RNA-sequencing studies from ArrayExpress, which have been manually curated, annotated with ontology terms, checked for high quality and processed using standardised analysis methods. Since the last update, Atlas has grown seven-fold (1572 studies as of August 2015), and incorporates baseline expression profiles of tissues from Human Protein Atlas, GTEx and FANTOM5, and of cancer cell lines from ENCODE, CCLE and Genentech projects. Plant studies constitute a quarter of Atlas data. For genes of interest, the user can view baseline expression in tissues, and differential expression for biologically meaningful pairwise comparisons-estimated using consistent methodology across all of Atlas. Our first proteomics study in human tissues is now displayed alongside transcriptomics data in the same tissues. Novel analyses and visualisations include: 'enrichment' in each differential comparison of GO terms, Reactome, Plant Reactome pathways and InterPro domains; hierarchical clustering (by baseline expression) of most variable genes and experimental conditions; and, for a given gene-condition, distribution of baseline expression across biological replicates.


Subject(s)
Databases, Genetic , Gene Expression Profiling , Plants/metabolism , Proteins/metabolism , Proteomics , Animals , Cell Line, Tumor , Humans , Plants/genetics , User-Computer Interface
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