Cited by 1,086

The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.

The Ensembl gene annotation system

Aken, Bronwen L., Ayling, Sarah, Barrell, Daniel, Clarke, Laura, Curwen, Valery, Fairley, Susan, Fernandez Banet, Julio, Billis, Konstantinos, García Girón, Carlos, Hourlier, Thibaut, Howe, Kevin, Kähäri, Andreas, Kokocinski, Felix, Martin, Fergal J., Murphy, Daniel N., Nag, Rishi, Ruffier, Magali, Schuster, Michael, Tang, Y. Amy, Vogel, Jan-Hinnerk, White, Simon, Zadissa, Amonida, Flicek, Paul, Searle, Stephen M. J.·2016·Database

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/database/baw093

Cites

17 of 17 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 main difference between NCBI's EGAP and Ensembl's Gene annotation system is the way in which they incorporate several lines of evidence into the end gene model results.

    “The main difference between NCBI’s Eukaryotic Genome Annotation Pipeline (EGAP) and Ensembl’s Gene annotation system is the way in which they incorporate several lines of evidence into the end gene model results.”
  • Ensembl and NCBI eukaryotic gene annotation pipelines have stringent requirements to include a solely ab initio model in their final gene set.

    “Indeed, the Ensembl and NCBI eukaryotic gene annotation pipelines have stringent requirements to include a solely ab initio model in their final gene set (Aken et al. 2016, Goldfarb et al. 2025).”

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: 87

  1. 10.1101/gr.1860604 · DOI
  2. Guigó, 2006, EGASP: the human ENCODE Genome Annotation Assessment Project, Genome Biol, 7(Suppl 1), S2.1
  3. 10.1101/gr.3866105 · DOI
  4. 10.1101/gr.135350.111 · DOI · Paper page
  5. Frankish, 2015, Comparison of GENCODE and RefSeq gene annotation and the impact of reference geneset on variant effect prediction, BMC Genomics, 16, S2., 10.1186/1471-2164-16-S8-S2 · DOI
  6. Ma C.X. Luo J. Naughton M. . (2015) A phase 1 trial of BKM120 (Buparlisib) in combination with fulvestrant in postmenopausal women with estrogen receptor positive metastatic breast cancer. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res., 22, 1583–1591. · DOI
  7. 10.7554/eLife.07405 · DOI
  8. 10.1093/hmg/ddu137 · DOI
  9. 10.1093/molbev/msv016 · DOI
  10. 10.1038/srep11487 · DOI
  11. 10.1038/ng.3098 · DOI
  12. 10.1371/journal.pone.0048650 · DOI
  13. 10.1371/journal.pone.0090074 · DOI
  14. 10.1016/j.ympev.2015.08.019 · DOI
  15. 10.1073/pnas.1510802112 · DOI
  16. 10.1101/gr.177840.114 · DOI
  17. 10.1038/nrg3174 · DOI · Paper page
  18. 10.1186/gm543 · DOI
  19. 10.1038/ng.2657 · DOI
  20. 10.1038/nature10390 · DOI
  21. 10.1038/ncomms6307 · DOI
  22. 10.1038/nature10342 · DOI
  23. 10.1038/nature10944 · DOI
  24. 10.1038/nature10842 · DOI
  25. 10.1038/nature12027 · DOI
  26. 10.1186/gb-2011-12-8-r81 · DOI
  27. 10.1038/nature05805 · DOI · Paper page
  28. 10.1038/nbt.3079 · DOI
  29. 10.1038/nature13679 · DOI
  30. 10.1038/nature13726 · DOI
  31. 10.1038/ng.2568 · DOI
  32. 10.1038/nature09687 · DOI
  33. 10.1038/nature02426 · DOI
  34. 10.1016/j.cell.2011.11.065 · DOI
  35. 10.1038/nature11622 · DOI
  36. 10.1038/nature08819 · DOI
  37. 10.1038/ng.2604 · DOI
  38. 10.1038/nmeth.3290 · DOI
  39. 10.1038/507294a · DOI
  40. 10.1093/nar/30.1.38 · DOI
  41. 10.1093/nar/gkt1030 · DOI
  42. 10.1093/nar/gks1175 · DOI
  43. 10.1093/nar/gkt1066 · DOI
  44. 10.1101/gr.1857204 · DOI
  45. 10.1101/gr.1859804 · DOI
  46. 10.1089/cmb.2006.13.1028 · DOI
  47. 10.1159/000084979 · DOI
  48. 10.1093/nar/gkt1140 · DOI
  49. 10.1006/jmbi.1997.0951 · DOI
  50. 10.1101/gr.216102 · DOI
  51. 10.1093/nar/25.5.0955 · DOI
  52. 10.1038/ng780 · DOI
  53. 10.1101/gr.1865504 · DOI · Paper page
  54. 10.1093/nar/gkt1114 · DOI
  55. 10.1186/1471-2105-6-31 · DOI
  56. 10.1016/0022-2836(82)90398-9 · DOI
  57. Kircher M. Kelso J. High-throughput DNA sequencing–concepts and limitations. Bioassays, 32, 524–536. · DOI
  58. 10.1101/gr.137901.112 · DOI
  59. Schwartz, 2002, Human–mouse alignments with BLASTZ, Genome Res, 13, 103, 10.1101/gr.809403 · DOI
  60. 10.1073/pnas.1932072100 · DOI · Paper page
  61. 10.1038/nmeth733 · DOI
  62. 10.1126/science.1112014 · DOI
  63. 10.1093/nar/gkj088 · DOI
  64. 10.1093/bfgp/elp042 · DOI
  65. 10.1093/nar/gkn766 · DOI
  66. 10.1186/1471-2105-3-18 · DOI
  67. 10.1093/nar/gkj112 · DOI · Paper page
  68. Denman, 1993, Using RNAFOLD to predict the activity of small catalytic RNAs, BioTechniques, 15, 1090
  69. Zerbino D.R. Johnson N. Juettemann T. . (2016) Ensembl regulation resources. Database (Oxford), 2016, bav119. · DOI
  70. 10.1093/nar/gkl1043 · DOI
  71. 10.1101/gr.080531.108 · DOI
  72. 10.1093/database/bas008 · DOI
  73. 10.1093/nar/gks1066 · DOI
  74. 10.1093/nar/gkt1168 · DOI · Paper page
  75. 10.1093/nar/gku1205 · DOI · Paper page
  76. 10.1016/0097-8485(93)85006-X · DOI
  77. Nielsen, 1998, Prediction of signal peptides and signal anchors by a hidden Markov model, Proc. Int. Conf. Intell. Syst. Mol. Biol. ISMB Int. Conf. Intell. Syst. Mol. Biol, 6, 122
  78. 10.1126/science.252.5009.1162 · DOI · Paper page
  79. 10.1006/jmbi.2000.4315 · DOI · Paper page
  80. Attwood, 2012, The PRINTS database: a fine-grained protein sequence annotation and analysis resource–its status in 2012, Database J. Biol. Databases Curation, 2012, bas019.
  81. 10.1093/nar/gks1067 · DOI
  82. 10.1093/nar/gkt1223 · DOI · Paper page
  83. 10.1006/jmbi.2001.5080 · DOI
  84. 10.1093/nar/gkj079 · DOI
  85. 10.1093/nar/gkh097 · DOI
  86. 10.1371/journal.pbio.1001091 · DOI
  87. 10.1093/jhered/esp086 · DOI

Cited by

Sorted by citations

Metadata

Authors
Aken, B. L., Ayling, S., Barrell, D., Clarke, L., Curwen, V., Fairley, S., Fernandez Banet, J., Billis, K., García Girón, C., Hourlier, T., Howe, K., Kähäri, A., Kokocinski, F., Martin, F. J., Murphy, D. N., Nag, R., Ruffier, M., Schuster, M., Tang, Y. A., Vogel, J.-H., White, S., Zadissa, A., Flicek, P., & Searle, S. M. J.
Venue
Database
Published
2016
Volume
2016
Pages
baw093
ISSN
1758-0463
Cited by
1,086
References
17
Language
en

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