The Experts below are selected from a list of 11964 Experts worldwide ranked by ideXlab platform
Sam Griffithsjones - One of the best experts on this subject based on the ideXlab platform.
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MiRBase from microrna sequences to function
Nucleic Acids Research, 2019Co-Authors: Ana Kozomara, Maria Birgaoanu, Sam GriffithsjonesAbstract:MiRBase catalogs, names and distributes microRNA gene sequences. The latest release of MiRBase (v22) contains microRNA sequences from 271 organisms: 38 589 hairpin precursors and 48 860 mature microRNAs. We describe improvements to the database and website to provide more information about the quality of microRNA gene annotations, and the cellular functions of their products. We have collected 1493 small RNA deep sequencing datasets and mapped a total of 5.5 billion reads to microRNA sequences. The read mapping patterns provide strong support for the validity of between 20% and 65% of microRNA annotations in different well-studied animal genomes, and evidence for the removal of >200 sequences from the database. To improve the availability of microRNA functional information, we are disseminating Gene Ontology terms annotated against MiRBase sequences. We have also used a text-mining approach to search for microRNA gene names in the full-text of open access articles. Over 500 000 sentences from 18 542 papers contain microRNA names. We score these sentences for functional information and link them with 12 519 microRNA entries. The sentences themselves, and word clouds built from them, provide effective summaries of the functional information about specific microRNAs. MiRBase is publicly and freely available at http://MiRBase.org/.
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MiRBase annotating high confidence micrornas using deep sequencing data
Nucleic Acids Research, 2014Co-Authors: Ana Kozomara, Sam GriffithsjonesAbstract:We describe an update of the MiRBase database (http://www.MiRBase.org/), the primary microRNA sequence repository. The latest MiRBase release (v20, June 2013) contains 24 521 microRNA loci from 206 species, processed to produce 30 424 mature microRNA products. The rate of deposition of novel microRNAs and the number of researchers involved in their discovery continue to increase, driven largely by small RNA deep sequencing experiments. In the face of these increases, and a range of microRNA annotation methods and criteria, maintaining the quality of the microRNA sequence data set is a significant challenge. Here, we describe recent developments of the MiRBase database to address this issue. In particular, we describe the collation and use of deep sequencing data sets to assign levels of confidence to MiRBase entries. We now provide a high confidence subset of MiRBase entries, based on the pattern of mapped reads. The high confidence microRNA data set is available alongside the complete microRNA collection at http://www.MiRBase.org/. We also describe embedding microRNA-specific Wikipedia pages on the MiRBase website to encourage the microRNA community to contribute and share textual and functional information.
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MiRBase integrating microrna annotation and deep sequencing data
Nucleic Acids Research, 2011Co-Authors: Ana Kozomara, Sam GriffithsjonesAbstract:MiRBase is the primary online repository for all microRNA sequences and annotation. The current release (MiRBase 16) contains over 15,000 microRNA gene loci in over 140 species, and over 17,000 distinct mature microRNA sequences. Deep-sequencing technologies have delivered a sharp rise in the rate of novel microRNA discovery. We have mapped reads from short RNA deep-sequencing experiments to microRNAs in MiRBase and developed web interfaces to view these mappings. The user can view all read data associated with a given microRNA annotation, filter reads by experiment and count, and search for microRNAs by tissue- and stage-specific expression. These data can be used as a proxy for relative expression levels of microRNA sequences, provide detailed evidence for microRNA annotations and alternative isoforms of mature microRNAs, and allow us to revisit previous annotations. MiRBase is available online at: http://www.MiRBase.org/.
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MiRBase microrna sequences and annotation
Current protocols in human genetics, 2010Co-Authors: Sam GriffithsjonesAbstract:MiRBase is the central repository for microRNA (miRNA) sequence information. MiRBase has a role in defining the nomenclature for miRNA genes and assigning names to novel miRNAs for publication in peer-reviewed journals. The online MiRBase database is a resource containing all published miRNA sequences, together with textual annotation and links to the primary literature and to other secondary databases. The database provides a variety of methods to query the data, by specific searches of sequences and associated text and literature. All MiRBase data are also available for download from the MiRBase FTP site. Curr. Protoc. Bioinform. 29:12.9.1-12.9.10. © 2010 by John Wiley & Sons, Inc. Keywords: microRNA; miRNA; MiRBase
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MiRBase tools for microrna genomics
Nucleic Acids Research, 2007Co-Authors: Sam Griffithsjones, Stijn Van Dongen, Harpreet K Saini, Anton J EnrightAbstract:MiRBase is the central online repository for microRNA (miRNA) nomenclature, sequence data, annotation and target prediction. The current release (10.0) contains 5071 miRNA loci from 58 species, expressing 5922 distinct mature miRNA sequences: a growth of over 2000 sequences in the past 2 years. MiRBase provides a range of data to facilitate studies of miRNA genomics: all miRNAs are mapped to their genomic coordinates. Clusters of miRNA sequences in the genome are highlighted, and can be defined and retrieved with any inter-miRNA distance. The overlap of miRNA sequences with annotated transcripts, both protein- and non-coding, are described. Finally, graphical views of the locations of a wide range of genomic features in model organisms allow for the first time the prediction of the likely boundaries of many miRNA primary transcripts. MiRBase is available at http://microrna.sanger.ac.uk/.
Sai Yendamuri - One of the best experts on this subject based on the ideXlab platform.
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evaluation of microrna expression profiles that may predict recurrence of localized stage i non small cell lung cancer after surgical resection
Cancer Research, 2010Co-Authors: Santosh K Patnaik, Eric Kannisto, Steen Knudsen, Sai YendamuriAbstract:Prognostic markers that can predict the relapse of localized non–small cell lung cancer (NSCLC) have yet to be defined. We surveyed expression profiles of microRNA (miRNA) in stage I NSCLC to identify patterns that might predict recurrence after surgical resection of this common deadly cancer. Small RNAs extracted from formalin-fixed and paraffin-embedded tissues were hybridized to locked nucleic acid probes against 752 human miRNAs (representing 82% of the miRNAs in the MiRBase 13.0 database) to obtain expression profiles for 37 cases with recurrence and 40 cases without recurrence (with clinical follow-up for at least 32 months). Differential expression between the two case groups was detected for 49% of the miRNAs (Wilcoxon rank sum test; P
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Evaluation of MicroRNA Expression Profiles That May Predict Recurrence of Localized Stage I Non–Small Cell Lung Cancer after Surgical Resection
Cancer research, 2009Co-Authors: Santosh K Patnaik, Eric Kannisto, Steen Knudsen, Sai YendamuriAbstract:Prognostic markers that can predict the relapse of localized non–small cell lung cancer (NSCLC) have yet to be defined. We surveyed expression profiles of microRNA (miRNA) in stage I NSCLC to identify patterns that might predict recurrence after surgical resection of this common deadly cancer. Small RNAs extracted from formalin-fixed and paraffin-embedded tissues were hybridized to locked nucleic acid probes against 752 human miRNAs (representing 82% of the miRNAs in the MiRBase 13.0 database) to obtain expression profiles for 37 cases with recurrence and 40 cases without recurrence (with clinical follow-up for at least 32 months). Differential expression between the two case groups was detected for 49% of the miRNAs (Wilcoxon rank sum test; P
Sam Griffiths-jones - One of the best experts on this subject based on the ideXlab platform.
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Quo vadis microRNAs
Trends in genetics : TIG, 2020Co-Authors: Bastian Fromm, Andreas Keller, Xiaozeng Yang, Marc R. Friedländer, Kevin J. Peterson, Sam Griffiths-jonesAbstract:Since 2002, published miRNAs have been collected and named by the online repository MiRBase. However, with 11 000 annual publications this has become challenging. Recently, four specialized miRNA databases were published, addressing particular needs for diverse scientific communities. This development provides major opportunities for the future of miRNA annotation and nomenclature.
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Current Protocols in Bioinformatics - MiRBase: microRNA sequences and annotation.
Current Protocols in Bioinformatics, 2010Co-Authors: Sam Griffiths-jonesAbstract:MiRBase is the central repository for microRNA (miRNA) sequence information. MiRBase has a role in defining the nomenclature for miRNA genes and assigning names to novel miRNAs for publication in peer-reviewed journals. The online MiRBase database is a resource containing all published miRNA sequences, together with textual annotation and links to the primary literature and to other secondary databases. The database provides a variety of methods to query the data, by specific searches of sequences and associated text and literature. All MiRBase data are also available for download from the MiRBase FTP site. Curr. Protoc. Bioinform. 29:12.9.1-12.9.10. © 2010 by John Wiley & Sons, Inc. Keywords: microRNA; miRNA; MiRBase
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MiRBase: microRNA sequences and annotation.
Current protocols in bioinformatics, 2010Co-Authors: Sam Griffiths-jonesAbstract:MiRBase is the central repository for microRNA (miRNA) sequence information. MiRBase has a role in defining the nomenclature for miRNA genes and assigning names to novel miRNAs for publication in peer-reviewed journals. The online MiRBase database is a resource containing all published miRNA sequences, together with textual annotation and links to the primary literature and to other secondary databases. The database provides a variety of methods to query the data, by specific searches of sequences and associated text and literature. All MiRBase data are also available for download from the MiRBase FTP site.
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MiRBase:The MicroRNA Sequence Database
Methods in molecular biology (Clifton N.J.), 2006Co-Authors: Sam Griffiths-jonesAbstract:The MiRBase Sequence database is the primary repository for published microRNA (miRNA) sequence and annotation data. MiRBase provides a user-friendly web interface for miRNA data, allowing the user to search using key words or sequences, trace links to the primary literature referencing the miRNA discoveries, analyze genomic coordinates and context, and mine relationships between miRNA sequences. MiRBase also provides a confidential gene-naming service, assigning official miRNA names to novel genes before their publication. The methods outlined in this chapter describe these functions. MiRBase is freely available to all at http://microrna.sanger.ac.uk/.
Andreas Keller - One of the best experts on this subject based on the ideXlab platform.
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mieaa 2 0 integrating multi species microrna enrichment analysis and workflow management systems
Nucleic Acids Research, 2020Co-Authors: Fabian Kern, Christina Backes, Tobias Fehlmann, Jeffrey Solomon, Louisa Schwed, Nadja Liddy Grammes, Kendall Van Keurenjensen, David Craig, Eckart Meese, Andreas KellerAbstract:Gene set enrichment analysis has become one of the most frequently used applications in molecular biology research. Originally developed for gene sets, the same statistical principles are now available for all omics types. In 2016, we published the miRNA enrichment analysis and annotation tool (miEAA) for human precursor and mature miRNAs. Here, we present miEAA 2.0, supporting miRNA input from ten frequently investigated organisms. To facilitate inclusion of miEAA in workflow systems, we implemented an Application Programming Interface (API). Users can perform miRNA set enrichment analysis using either the web-interface, a dedicated Python package, or custom remote clients. Moreover, the number of category sets was raised by an order of magnitude. We implemented novel categories like annotation confidence level or localisation in biological compartments. In combination with the MiRBase miRNA-version and miRNA-to-precursor converters, miEAA supports research settings where older releases of MiRBase are in use. The web server also offers novel comprehensive visualizations such as heatmaps and running sum curves with background distributions. We demonstrate the new features with case studies for human kidney cancer, a biomarker study on Parkinson's disease from the PPMI cohort, and a mouse model for breast cancer. The tool is freely accessible at: https://www.ccb.uni-saarland.de/mieaa2.
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Quo vadis microRNAs
Trends in genetics : TIG, 2020Co-Authors: Bastian Fromm, Andreas Keller, Xiaozeng Yang, Marc R. Friedländer, Kevin J. Peterson, Sam Griffiths-jonesAbstract:Since 2002, published miRNAs have been collected and named by the online repository MiRBase. However, with 11 000 annual publications this has become challenging. Recently, four specialized miRNA databases were published, addressing particular needs for diverse scientific communities. This development provides major opportunities for the future of miRNA annotation and nomenclature.
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mieaa 2 0 integrating multi species microrna enrichment analysis and workflow management systems
bioRxiv, 2020Co-Authors: Fabian Kern, Christina Backes, Tobias Fehlmann, Andreas Keller, Jeffrey Solomon, Louisa Schwed, Eckart MeeseAbstract:Gene set enrichment analysis has become one of the most frequently used applications in molecular biology research. Originally developed for gene sets, the same statistical principles are now available for all omics types. In 2016, we published the miRNA enrichment analysis and annotation tool (miEAA) for human precursor and mature miRNAs. Here, we present miEAA 2.0, supporting miRNA input from Homo sapiens, Mus musculus, and Rattus norvegicus. To facilitate inclusion of miEAA in workflow systems, we implemented an Application Programming Interface (API). Users can perform miRNA set enrichment analysis using either the web-interface, a dedicated Python package, or custom remote clients. Moreover, the number of category sets was raised by an order of magnitude. We implemented novel categories like annotation confidence level or localisation in biological compartments. In combination with the MiRBase miRNA-version and miRNA-to-precursor converters, miEAA supports research settings where older releases of MiRBase are in use. The web server also offers novel comprehensive visualisations such as heatmaps and running sum curves with background distributions. Lastly, additional methods to correct for multiple hypothesis testing were implemented. We demonstrate the new features using case studies for human kidney cancer and mouse samples. The tool is freely accessible at: https://www.ccb.uni-saarland.de/mieaa2 .
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Bias in recent MiRBase annotations potentially associated with RNA quality issues
Scientific reports, 2017Co-Authors: Nicole Ludwig, Tobias Fehlmann, Andreas Keller, Meike Becker, Timo Schumann, Timo Speer, Eckart MeeseAbstract:Although microRNAs are supposed to be stable in-vivo, degradation processes potentially blur our knowledge on the small oligonucleotides. We set to quantify the effect of degradation on microRNAs in mouse to identify causes for distorted microRNAs patterns. In liver, we found 298, 99 and 8 microRNAs whose expression significantly correlated to RNA integrity, storage time at room temperature and storage time at 4 °C, respectively. Expression levels of 226 microRNAs significantly differed between liver samples with high RNA integrity compared to liver samples with low RNA integrity by more than two-fold. Especially the 157 microRNAs with increased expression in tissue samples with low RNA integrity were most recently added to MiRBase. Testing potentially confounding sources, e.g. in-vitro degraded RNA depleted of small RNAs, we detected signals for 350 microRNAs, suggesting cross-hybridization of fragmented RNAs. Therefore, we conclude that especially microRNAs added in the latest MiRBase versions might be artefacts due to RNA degradation. The results facilitate differentiation between degradation-resilient microRNAs, degradation-sensitive microRNAs, and likely erroneously annotated microRNAs. The latter were largely identified by NGS but not experimentally validated and can severely bias microRNA biomarker research and impact the value of microRNAs as diagnostic, prognostic or therapeutic tools.
Anton J Enright - One of the best experts on this subject based on the ideXlab platform.
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MapMi: automated mapping of microRNA loci.
BMC bioinformatics, 2010Co-Authors: José Afonso Guerra-assunção, Anton J EnrightAbstract:A large effort to discover microRNAs (miRNAs) has been under way. Currently MiRBase is their primary repository, providing annotations of primary sequences, precursors and probable genomic loci. In many cases miRNAs are identical or very similar between related (or in some cases more distant) species. However, MiRBase focuses on those species for which miRNAs have been directly confirmed. Secondly, specific miRNAs or their loci are sometimes not annotated even in well-covered species. We sought to address this problem by developing a computational system for automated mapping of miRNAs within and across species. Given the sequence of a known miRNA in one species it is relatively straightforward to determine likely loci of that miRNA in other species. Our primary goal is not the discovery of novel miRNAs but the mapping of validated miRNAs in one species to their most likely orthologues in other species. We present MapMi, a computational system for automated miRNA mapping across and within species. This method has a sensitivity of 92.20% and a specificity of 97.73%. Using the latest release (v14) of MiRBase, we obtained 10,944 unannotated potential miRNAs when MapMi was applied to all 21 species in Ensembl Metazoa release 2 and 46 species from Ensembl release 55. The pipeline and an associated web-server for mapping miRNAs are freely available on http://www.ebi.ac.uk/enright-srv/MapMi/ . In addition precomputed miRNA mappings of MiRBase miRNAs across a large number of species are provided.
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MiRBase tools for microrna genomics
Nucleic Acids Research, 2007Co-Authors: Sam Griffithsjones, Stijn Van Dongen, Harpreet K Saini, Anton J EnrightAbstract:MiRBase is the central online repository for microRNA (miRNA) nomenclature, sequence data, annotation and target prediction. The current release (10.0) contains 5071 miRNA loci from 58 species, expressing 5922 distinct mature miRNA sequences: a growth of over 2000 sequences in the past 2 years. MiRBase provides a range of data to facilitate studies of miRNA genomics: all miRNAs are mapped to their genomic coordinates. Clusters of miRNA sequences in the genome are highlighted, and can be defined and retrieved with any inter-miRNA distance. The overlap of miRNA sequences with annotated transcripts, both protein- and non-coding, are described. Finally, graphical views of the locations of a wide range of genomic features in model organisms allow for the first time the prediction of the likely boundaries of many miRNA primary transcripts. MiRBase is available at http://microrna.sanger.ac.uk/.
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MiRBase microrna sequences targets and gene nomenclature
Nucleic Acids Research, 2006Co-Authors: Sam Griffithsjones, Russell J Grocock, Stijn Van Dongen, Alex Bateman, Anton J EnrightAbstract:The MiRBase database aims to provide integrated interfaces to comprehensive microRNA sequence data, annotation and predicted gene targets. MiRBase takes over functionality from the microRNA Registry and fulfils three main roles: the MiRBase Registry acts as an independent arbiter of microRNA gene nomenclature, assigning names prior to publication of novel miRNA sequences. MiRBase Sequences is the primary online repository for miRNA sequence data and annotation. MiRBase Targets is a comprehensive new database of predicted miRNA target genes. MiRBase is available at http://microrna.sanger.ac.uk/.