49 research outputs found

    Conceptual Model of Resolution

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    In this document, we look at three aspects of the resolution of identifiers to a URI representing the resource: dynamic data citation, content negotiation, and machine-enabled licence information

    CellPhoneDB v5: inferring cell-cell communication from single-cell multiomics data

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    Cell-cell communication is essential for tissue development, regeneration and function, and its disruption can lead to diseases and developmental abnormalities. The revolution of single-cell genomics technologies offers unprecedented insights into cellular identities, opening new avenues to resolve the intricate cellular interactions present in tissue niches. CellPhoneDB is a bioinformatics toolkit designed to infer cell-cell communication by combining a curated repository of bona fide ligand-receptor interactions with a set of computational and statistical methods to integrate them with single-cell genomics data. Importantly, CellPhoneDB captures the multimeric nature of molecular complexes, thus representing cell-cell communication biology faithfully. Here we present CellPhoneDB v5, an updated version of the tool, which offers several new features. Firstly, the repository has been expanded by one-third with the addition of new interactions. These encompass interactions mediated by non-protein ligands such as endocrine hormones and GPCR ligands. Secondly, it includes a differentially expression-based methodology for more tailored interaction queries. Thirdly, it incorporates novel computational methods to prioritise specific cell-cell interactions, leveraging other single-cell modalities, such as spatial information or TF activities (i.e. CellSign module). Finally, we provide CellPhoneDBViz, a module to interactively visualise and share results amongst users. Altogether, CellPhoneDB v5 elevates the precision of cell-cell communication inference, ushering in new perspectives to comprehend tissue biology in both healthy and pathological states.Comment: 30 pages, 3 figures and 2 tables. Added previously missing figures and tables; Updated the reference for 'An integrated single-cell reference atlas of the human endometrium' pape

    Demonstrating public value to funders and other stakeholders—the journey of ELIXIR, a virtual and distributed research infrastructure for life science data

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    Open Science is a founding principle of ELIXIR, a pan-European research infrastructure for life science data, with 21 Member countries plus the European Molecular Biology Laboratory. The mission of ELIXIR is to coordinate bioinformatics resources so that they form a single, integrated and pan-European infrastructure, which can be used freely by academic and private-sector researchers across the globe. As a recipient of public and charitable funding, ELIXIR must demonstrate its value, and the need to produce evidence in support of this is intensifying. Our practice-led journey towards demonstrating public value is articulated around five main challenges and, for each, we present our pragmatic approach for tackling it. We begin by showing how we are working towards demystifying what research infrastructures do. We then shed light on the sort of evidence our funders and other stakeholders are asking us for, how this evidence varies in nature and scope, and our tactics to satisfy them. We follow-on by providing our thoughts on possible barriers and solutions to embedding impact evaluation in our activities. Finally, we provide lessons learned, which we believe are sufficiently transferable and will be inspirational to other research infrastructures as they embark on their own journeys to demonstrate public value.publishedVersio

    Integr8 and Genome Reviews: integrated views of complete genomes and proteomes

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    Integr8 is a new web portal for exploring the biology of organisms with completely deciphered genomes. For over 190 species, Integr8 provides access to general information, recent publications, and a detailed statistical overview of the genome and proteome of the organism. The preparation of this analysis is supported through Genome Reviews, a new database of bacterial and archaeal DNA sequences in which annotation has been upgraded (compared to the original submission) through the integration of data from many sources, including the EMBL Nucleotide Sequence Database, the UniProt Knowledgebase, InterPro, CluSTr, GOA and HOGENOM. Integr8 also allows the users to customize their own interactive analysis, and to download both customized and prepared datasets for their own use. Integr8 is available at http://www.ebi.ac.uk/integr

    Integr8 and Genome Reviews: integrated views of complete genomes and proteomes

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    Integr8 is a new web portal for exploring the biology of organisms with completely deciphered genomes. For over 190 species, Integr8 provides access to general information, recent publications, and a detailed statistical overview of the genome and proteome of the organism. The preparation of this analysis is supported through Genome Reviews, a new database of bacterial and archaeal DNA sequences in which annotation has been upgraded (compared to the original submission) through the integration of data from many sources, including the EMBL Nucleotide Sequence Database, the UniProt Knowledgebase, InterPro, CluSTr, GOA and HOGENOM. Integr8 also allows the users to customize their own interactive analysis, and to download both customized and prepared datasets for their own use. Integr8 is available at http://www.ebi.ac.uk/integr8

    GeMMA: functional subfamily classification within superfamilies of predicted protein structural domains

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    GeMMA (Genome Modelling and Model Annotation) is a new approach to automatic functional subfamily classification within families and superfamilies of protein sequences. A major advantage of GeMMA is its ability to subclassify very large and diverse superfamilies with tens of thousands of members, without the need for an initial multiple sequence alignment. Its performance is shown to be comparable to the established high-performance method SCI-PHY. GeMMA follows an agglomerative clustering protocol that uses existing software for sensitive and accurate multiple sequence alignment and profile–profile comparison. The produced subfamilies are shown to be equivalent in quality whether whole protein sequences are used or just the sequences of component predicted structural domains. A faster, heuristic version of GeMMA that also uses distributed computing is shown to maintain the performance levels of the original implementation. The use of GeMMA to increase the functional annotation coverage of functionally diverse Pfam families is demonstrated. It is further shown how GeMMA clusters can help to predict the impact of experimentally determining a protein domain structure on comparative protein modelling coverage, in the context of structural genomics

    New developments in the InterPro database

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    InterPro is an integrated resource for protein families, domains and functional sites, which integrates the following protein signature databases: PROSITE, PRINTS, ProDom, Pfam, SMART, TIGRFAMs, PIRSF, SUPERFAMILY, Gene3D and PANTHER. The latter two new member databases have been integrated since the last publication in this journal. There have been several new developments in InterPro, including an additional reading field, new database links, extensions to the web interface and additional match XML files. InterPro has always provided matches to UniProtKB proteins on the website and in the match XML file on the FTP site. Additional matches to proteins in UniParc (UniProt archive) are now available for download in the new match XML files only. The latest InterPro release (13.0) contains more than 13 000 entries, covering over 78% of all proteins in UniProtKB. The database is available for text- and sequence-based searches via a webserver (), and for download by anonymous FTP (). The InterProScan search tool is now also available via a web service at

    Discovering and linking public omics data sets using the Omics Discovery Index.

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    Biomedical data are being produced at an unprecedented rate owing to the falling cost of experiments and wider access to genomics, transcriptomics, proteomics and metabolomics platforms1, 2. As a result, public deposition of omics data is on the increase. This presents new challenges, including finding ways to store, organize and access different types of biomedical data stored on different platforms. Here, we present the Omics Discovery Index (OmicsDI; http://www.omicsdi.org), an open-source platform that enables access, discovery and dissemination of omics data sets

    Expression Atlas update--a database of gene and transcript expression from microarray- and sequencing-based functional genomics experiments.

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    Expression Atlas (http://www.ebi.ac.uk/gxa) is a value-added database providing information about gene, protein and splice variant expression in different cell types, organism parts, developmental stages, diseases and other biological and experimental conditions. The database consists of selected high-quality microarray and RNA-sequencing experiments from ArrayExpress that have been manually curated, annotated with Experimental Factor Ontology terms and processed using standardized microarray and RNA-sequencing analysis methods. The new version of Expression Atlas introduces the concept of 'baseline' expression, i.e. gene and splice variant abundance levels in healthy or untreated conditions, such as tissues or cell types. Differential gene expression data benefit from an in-depth curation of experimental intent, resulting in biologically meaningful 'contrasts', i.e. instances of differential pairwise comparisons between two sets of biological replicates. Other novel aspects of Expression Atlas are its strict quality control of raw experimental data, up-to-date RNA-sequencing analysis methods, expression data at the level of gene sets, as well as genes and a more powerful search interface designed to maximize the biological value provided to the user

    Expression Atlas: gene and protein expression across multiple studies and organisms

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    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
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