CoChat
Sign Up
Cited by 419

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

RNAcentral 2021: secondary structure integration, improved sequence search and new member databases

RNAcentral Consortium, Sweeney, Blake A, Petrov, Anton I, Ribas, Carlos E, Finn, Robert D, Bateman, Alex, Szymanski, Maciej, Karlowski, Wojciech M, Seemann, Stefan E, Gorodkin, Jan, Cannone, Jamie J, Gutell, Robin R, Kay, Simon, Marygold, Steven, dos Santos, Gil, Frankish, Adam, Mudge, Jonathan M, Barshir, Ruth, Fishilevich, Simon, Chan, Patricia P, Lowe, Todd M, Seal, Ruth, Bruford, Elspeth, Panni, Simona, Porras, Pablo, Karagkouni, Dimitra, Hatzigeorgiou, Artemis G, Ma, Lina, Zhang, Zhang, Volders, Pieter-Jan, Mestdagh, Pieter, Griffiths-Jones, Sam, Fromm, Bastian, Peterson, Kevin J, Kalvari, Ioanna, Nawrocki, Eric P, Petrov, Anton S, Weng, Shuai, Bouchard-Bourelle, Philia, Scott, Michelle, Lui, Lauren M, Hoksza, David, Lovering, Ruth C, Kramarz, Barbara, Mani, Prita, Ramachandran, Sridhar, Weinberg, Zasha·2021·Nucleic Acids Research
DOI 10.1093/nar/gkaa921PMC PMC7779037
Open this paper in CoChat — free account

Abstract

RNAcentral is a comprehensive database of non-coding RNA (ncRNA) sequences that provides a single access point to 44 RNA resources and >18 million ncRNA sequences from a wide range of organisms and RNA types. RNAcentral now also includes secondary (2D) structure information for >13 million sequences, making RNAcentral the world’s largest RNA 2D structure database. The 2D diagrams are displayed using R2DT, a new 2D structure visualization method that uses consistent, reproducible and recognizable layouts for related RNAs. The sequence similarity search has been updated with a faster interface featuring facets for filtering search results by RNA type, organism, source database or any keyword. This sequence search tool is available as a reusable web component, and has been integrated into several RNAcentral member databases, including Rfam, miRBase and snoDB. To allow for a more fine-grained assignment of RNA types and subtypes, all RNAcentral sequences have been annotated with Sequence Ontology terms. The RNAcentral database continues to grow and provide a central data resource for the RNA community. RNAcentral is freely available at https://rnacentral.org.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/nar/gkaa921

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The following ncRNA databases are included in the analysis: miRBase version 22.1, Ensembl ncRNA version 100, RNACentral version 15, GtRNAdb version 18.1 and NONCODE version 5.

    “The following ncRNA databases are included in our analysis: miRBase version 22.1 (16), Ensembl ncRNA version 100 (44), RNACentral version 15 (45), GtRNAdb version 18.1 (17) and NONCODE version 5 (46).”

    From miRNATissueAtlas2: an update to the human miRNA tissue atlas (2022) · cites this paper as [45]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 44

  1. RNAcentral Consortium, 2019, RNAcentral: a hub of information for non-coding RNA sequences, Nucleic Acids Res., 47, D221, 10.1093/nar/gky1034 · DOI
  2. Karagkouni, 2018, DIANA-TarBase v8: a decade-long collection of experimentally supported miRNA–gene interactions, Nucleic Acids Res., 46, D239, 10.1093/nar/gkx1141 · DOI · Paper page
  3. Paraskevopoulou, 2016, DIANA-LncBase v2: indexing microRNA targets on non-coding transcripts, Nucleic Acids Res., 44, D231, 10.1093/nar/gkv1270 · DOI
  4. Binns, 2009, QuickGO: a web-based tool for Gene Ontology searching, Bioinformatics, 25, 3045, 10.1093/bioinformatics/btp536 · DOI · Paper page
  5. Pignatelli, 2016, ncRNA orthologies in the vertebrate lineage, Database:J. Biol. Database. Curat., 2016, bav127, 10.1093/database/bav127 · DOI
  6. Kalvari, 2017, Rfam 13.0: shifting to a genome-centric resource for non-coding RNA families, Nucleic Acids Res., 46, D335, 10.1093/nar/gkx1038 · DOI
  7. Chan, 2016, GtRNAdb 2.0: an expanded database of transfer RNA genes identified in complete and draft genomes, Nucleic Acids Res., 44, D184, 10.1093/nar/gkv1309 · DOI
  8. Cannone, 2002, The Comparative RNA Web (CRW) Site: an online database of comparative sequence and structure information for ribosomal, intron, and other RNAs, BMC Bioinformatics, 3, 2, 10.1186/1471-2105-3-2 · DOI
  9. Holley, 1965, STRUCTURE OF A RIBONUCLEIC ACID, Science, 147, 1462, 10.1126/science.147.3664.1462 · DOI
  10. Sweeney, 2020, R2DT: computational framework for template-based RNA secondary structure visualisation across non-coding RNA types, 10.1101/2020.09.10.290924 · DOI
  11. Chan, 2019, tRNAscan-SE 2.0: Improved Detection and Functional Classification of Transfer RNA Genes, 10.1101/614032 · DOI
  12. Elias, 2017, TRAVeLer: a tool for template-based RNA secondary structure visualization, BMC Bioinformatics, 18, 487, 10.1186/s12859-017-1885-4 · DOI
  13. Bernier, 2014, RiboVision suite for visualization and analysis of ribosomes, Faraday Discuss., 169, 195, 10.1039/C3FD00126A · DOI
  14. Wheeler, 2013, nhmmer: DNA homology search with profile HMMs, Bioinformatics, 29, 2487, 10.1093/bioinformatics/btt403 · DOI
  15. Nawrocki, 2013, Infernal 1.1: 100-fold faster RNA homology searches, Bioinformatics, 29, 2933, 10.1093/bioinformatics/btt509 · DOI
  16. Kozomara, 2019, miRBase: from microRNA sequences to function, Nucleic Acids Res., 47, D155, 10.1093/nar/gky1141 · DOI · Paper page
  17. Bouchard-Bourelle, 2020, snoDB: an interactive database of human snoRNA sequences, abundance and interactions, Nucleic Acids Res., 48, D220, 10.1093/nar/gkz884 · DOI
  18. Eilbeck, 2005, The Sequence Ontology: a tool for the unification of genome annotations, Genome Biol., 6, R44, 10.1186/gb-2005-6-5-r44 · DOI · Paper page
  19. Ma, 2019, LncBook: a curated knowledgebase of human long non-coding RNAs, Nucleic Acids Res., 47, D128, 10.1093/nar/gky960 · DOI
  20. Stelzer, 2016, The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analyses, Curr. Protoc. Bioinformatics, 54, 1.30.1, 10.1002/cpbi.5 · DOI · Paper page
  21. Rappaport, 2017, MalaCards: an amalgamated human disease compendium with diverse clinical and genetic annotation and structured search, Nucleic Acids Res., 45, D877, 10.1093/nar/gkw1012 · DOI
  22. Alliance of Genome Resources Consortium, 2019, The alliance of genome Resources: Building a modern data ecosystem for model organism databases, Genetics, 213, 1189, 10.1534/genetics.119.302523 · DOI
  23. Ruzicka, 2019, The Zebrafish Information Network: new support for non-coding genes, richer Gene Ontology annotations and the Alliance of Genome Resources, Nucleic Acids Res., 47, D867, 10.1093/nar/gky1090 · DOI
  24. Howe, 2020, Ensembl Genomes 2020—enabling non-vertebrate genomic research, Nucleic Acids Res., 48, D689, 10.1093/nar/gkz890 · DOI
  25. Orchard, 2014, The MIntAct project–IntAct as a common curation platform for 11 molecular interaction databases, Nucleic Acids Res., 42, D358, 10.1093/nar/gkt1115 · DOI
  26. Huntley, 2018, Expanding the horizons of microRNA bioinformatics, RNA, 24, 1005, 10.1261/rna.065565.118 · DOI
  27. Kramarz, 2020, Gene ontology curation of neuroinflammation biology improves the interpretation of Alzheimer's disease gene expression data, J. Alzheimers. Dis., 75, 1417, 10.3233/JAD-200207 · DOI
  28. Szymanski, 2016, 5SRNAdb: an information resource for 5S ribosomal RNAs, Nucleic Acids Res., 44, D180, 10.1093/nar/gkv1081 · DOI
  29. Lui, 2018, Methylation guide RNA evolution in archaea: structure, function and genomic organization of 110 C/D box sRNA families across six Pyrobaculum species, Nucleic Acids Res., 46, 5678, 10.1093/nar/gky284 · DOI
  30. Omer, 2000, Homologs of small nucleolar RNAs in Archaea, Science, 288, 517, 10.1126/science.288.5465.517 · DOI
  31. Fromm, 2020, MirGeneDB 2.0: the metazoan microRNA complement, Nucleic Acids Res., 48, D1172, 10.1093/nar/gkz885 · DOI · Paper page
  32. Eckert, 2020, Discovery of 20 novel ribosomal leader candidates in bacteria and archaea, BMC Microbiol., 20, 130, 10.1186/s12866-020-01823-6 · DOI
  33. Seemann, 2017, The identification and functional annotation of RNA structures conserved in vertebrates, Genome Res., 27, 1371, 10.1101/gr.208652.116 · DOI
  34. Quast, 2013, The SILVA ribosomal RNA gene database project: improved data processing and web-based tools, Nucleic Acids Res., 41, D590, 10.1093/nar/gks1219 · DOI · Paper page
  35. Thurmond, 2019, FlyBase 2.0: the next generation, Nucleic Acids Res., 47, D759, 10.1093/nar/gky1003 · DOI
  36. Braschi, 2019, Genenames.org: the HGNC and VGNC resources in 2019, Nucleic Acids Res., 47, D786, 10.1093/nar/gky930 · DOI
  37. Rom, 2019, Regulation of CHD2 expression by the Chaserr long noncoding RNA gene is essential for viability, Nat. Commun., 10, 5092, 10.1038/s41467-019-13075-8 · DOI
  38. Hitachi, 2019, Myogenin promoter-associated lncRNA Myoparr is essential for myogenic differentiation, EMBO Rep., 20, 10.15252/embr.201847468 · DOI
  39. Sirey, 2019, The long non-coding RNA Cerox1 is a post transcriptional regulator of mitochondrial complex I catalytic activity, Elife, 8, e45051, 10.7554/eLife.45051 · DOI
  40. Sirey, 2019, Correction: The long non-coding RNA Cerox1 is a post transcriptional regulator of mitochondrial complex I catalytic activity, Elife, 8, e50980, 10.7554/eLife.50980 · DOI
  41. Seal, 2020, A guide to naming human non-coding RNA genes, EMBO J., 39, e103777, 10.15252/embj.2019103777 · DOI
  42. Volders, 2019, LNCipedia 5: towards a reference set of human long non-coding RNAs, Nucleic Acids Res., 47, D135, 10.1093/nar/gky1031 · DOI · Paper page
  43. Yates, 2020, Ensembl 2020, Nucleic Acids Res., 48, D682
  44. Sweeney, 2020, Exploring Non-Coding RNAs in RNAcentral, Curr. Protoc. Bioinformatics, 71, e104, 10.1002/cpbi.104 · DOI

Cited by

Sorted by citations

Metadata

Authors
RNAcentral Consortium, Sweeney, B. A., Petrov, A. I., Ribas, C. E., Finn, R. D., Bateman, A., Szymanski, M., Karlowski, W. M., Seemann, S. E., Gorodkin, J., Cannone, J. J., Gutell, R. R., Kay, S., Marygold, S., dos Santos, G., Frankish, A., Mudge, J. M., Barshir, R., Fishilevich, S., Chan, P. P., Lowe, T. M., Seal, R., Bruford, E., Panni, S., Porras, P., Karagkouni, D., Hatzigeorgiou, A. G., Ma, L., Zhang, Z., Volders, P.-J., Mestdagh, P., Griffiths-Jones, S., Fromm, B., Peterson, K. J., Kalvari, I., Nawrocki, E. P., Petrov, A. S., Weng, S., Bouchard-Bourelle, P., Scott, M., Lui, L. M., Hoksza, D., Lovering, R. C., Kramarz, B., Mani, P., Ramachandran, S., & Weinberg, Z.
Venue
Nucleic Acids Research
Publisher
Oxford University Press (OUP)
Published
2020-10-27
Volume
49
Issue
D1
Pages
D212-D220
ISSN
  • 0305-1048
  • 1362-4962
DOI
10.1093/nar/gkaa921
PMC
PMC7779037
Cited by
419
References
2
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (vor)
Funders
  • Biotechnology and Biological Sciences Research Council (BB/N019199/1)
  • Wellcome Trust (218302/Z/19/Z, 208349/Z/17/Z)
  • National Institutes of Health (U24HG003345, U41HG000739)
  • Charles University (SVV 260588)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review