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      RBP2GO: a comprehensive pan-species database on RNA-binding proteins, their interactions and functions

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      , , ,
      Nucleic Acids Research
      Oxford University Press

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          Abstract

          RNA–protein complexes have emerged as central players in numerous key cellular processes with significant relevance in health and disease. To further deepen our knowledge of RNA-binding proteins (RBPs), multiple proteome-wide strategies have been developed to identify RBPs in different species leading to a large number of studies contributing experimentally identified as well as predicted RBP candidate catalogs. However, the rapid evolution of the field led to an accumulation of isolated datasets, hampering the access and comparison of their valuable content. Moreover, tools to link RBPs to cellular pathways and functions were lacking. Here, to facilitate the efficient screening of the RBP resources, we provide RBP2GO ( https://RBP2GO.DKFZ.de), a comprehensive database of all currently available proteome-wide datasets for RBPs across 13 species from 53 studies including 105 datasets identifying altogether 22 552 RBP candidates. These are combined with the information on RBP interaction partners and on the related biological processes, molecular functions and cellular compartments. RBP2GO offers a user-friendly web interface with an RBP scoring system and powerful advanced search tools allowing forward and reverse searches connecting functions and RBPs to stimulate new research directions.

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          Graphical Abstract

          RBP2GO ( https://RBP2GO.DKFZ.de) is a comprehensive database of all currently available proteome-wide datasets for RNA-binding proteins, their functions and interaction partners.Question: is it necessary to have a caption for the graphical abstract? I cannot see them on the website or PDFs of the articles.

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          Most cited references53

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

            Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
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              UniProt: a worldwide hub of protein knowledge

              (2018)
              Abstract The UniProt Knowledgebase is a collection of sequences and annotations for over 120 million proteins across all branches of life. Detailed annotations extracted from the literature by expert curators have been collected for over half a million of these proteins. These annotations are supplemented by annotations provided by rule based automated systems, and those imported from other resources. In this article we describe significant updates that we have made over the last 2 years to the resource. We have greatly expanded the number of Reference Proteomes that we provide and in particular we have focussed on improving the number of viral Reference Proteomes. The UniProt website has been augmented with new data visualizations for the subcellular localization of proteins as well as their structure and interactions. UniProt resources are available under a CC-BY (4.0) license via the web at https://www.uniprot.org/.
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                Author and article information

                Contributors
                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                08 January 2021
                16 November 2020
                16 November 2020
                : 49
                : D1
                : D425-D436
                Affiliations
                Division of RNA Biology & Cancer, German Cancer Research Center (DKFZ) , 69120 Heidelberg, Germany
                Division of RNA Biology & Cancer, German Cancer Research Center (DKFZ) , 69120 Heidelberg, Germany
                Division of RNA Biology & Cancer, German Cancer Research Center (DKFZ) , 69120 Heidelberg, Germany
                Division of RNA Biology & Cancer, German Cancer Research Center (DKFZ) , 69120 Heidelberg, Germany
                Division of Cancer Research, Department of Thoracic Surgery, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg , German Cancer Consortium (DKTK) - Partner Site Freiburg, 79106 Freiburg, Germany
                Author notes
                To whom correspondence should be addressed. Tel: +49 6221 42 43 82; Email: m.caudron@ 123456dkfz.de
                Author information
                http://orcid.org/0000-0002-7030-8153
                http://orcid.org/0000-0001-7901-4752
                Article
                gkaa1040
                10.1093/nar/gkaa1040
                7778890
                33196814
                acc147b6-18c7-447f-917e-eb3b346de6ce
                © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 28 October 2020
                : 01 October 2020
                : 14 August 2020
                Page count
                Pages: 12
                Funding
                Funded by: German Cancer Aid, DOI 10.13039/501100005972;
                Award ID: 70113919
                Funded by: Wilhelm Sander-Stiftung, DOI 10.13039/100008672;
                Award ID: 2020.062.1
                Funded by: Baden-Württemberg Stiftung, DOI 10.13039/100008316;
                Award ID: BWF_ISF2019-027
                Categories
                AcademicSubjects/SCI00010
                Database Issue

                Genetics
                Genetics

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