Cited by 2,542

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

GeneWise and Genomewise

Birney, Ewan, Clamp, Michele, Durbin, Richard·2004·Genome Research

Abstract

We present two algorithms in this paper: GeneWise, which predicts gene structure using similar protein sequences, and Genomewise, which provides a gene structure final parse across cDNA- and EST-defined spliced structure. Both algorithms are heavily used by the Ensembl annotation system. The GeneWise algorithm was developed from a principled combination of hidden Markov models (HMMs). Both algorithms are highly accurate and can provide both accurate and complete gene structures when used with the correct evidence.

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 · 10.1101/gr.1865504

Cites

3 of 3 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 Ensembl annotation system predicts genes independently for each of its stages using GeneWise, in some cases in addition to previously predicted models using Genscan, and finally finds a consensus set of gene models.

    “On the other hand, the Ensembl annotation system predicts genes independently for each of its “stages” (targeted, similarity, species-specific cDNA and EST, RNA-seq reads) using the gene prediction tool “GeneWise” (Birney et al. 2004), in some cases in addition to previously predicted models using “Genscan”. Finally, it finds a consensus set of gene models coming from all stages.”

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: 25

  1. 10.1101/gr.424203 · DOI
  2. 10.1126/science.1072104 · DOI · Paper page
  3. 1997, ISMB, 97, 56
  4. 10.1101/gr.10.4.547 · DOI
  5. 10.1093/nar/24.14.2730 · DOI
  6. 10.1006/jmbi.1997.0951 · DOI
  7. 10.1093/bioinformatics/14.9.755 · DOI · Paper page
  8. 10.1101/gr.830003 · DOI
  9. 10.1038/nature01554 · DOI
  10. 10.1073/pnas.93.17.9061 · DOI
  11. 10.1101/gr.122800 · DOI
  12. 10.1038/nature01782 · DOI
  13. 1998, J. Comp. Biol., 5, 493, 10.1089/cmb.1998.5.493 · DOI
  14. 10.1101/gr.149502 · DOI
  15. 10.1038/35057062 · DOI · Paper page
  16. 10.1101/gr.10.4.523 · DOI
  17. Kulp, D., Haussler, D., Reese, M.G., and Eeckman, F.H. 1996. A generalized hidden Markov model for the recognition of human genes in DNA. In Proceedings of the fourth international conference on intelligent systems for molecular biology (eds. D.J. States et al.), pp. 134-142. AAAI Press, Menlo Park, CA.
  18. 10.1093/bioinformatics/18.10.1309 · DOI
  19. 1997, Comp. Appl. Biosci., 13, 477
  20. 10.1101/gr.871403 · DOI
  21. 10.1093/bioinformatics/19.2.219 · DOI
  22. Siepel, A. and Haussler, D. 2003. Combining phylogenetic and hidden markov models in biosequence analysis. In Proceedings of the seventh annual international conference on research in computational biology (RECOMB'03) 277-286. · DOI
  23. 1997, ISMB, 97, 294
  24. 10.1101/gr.175701 · DOI
  25. 10.1038/nrg890 · DOI

Cited by

Sorted by citations

Metadata

Authors
Birney, E., Clamp, M., & Durbin, R.
Venue
Genome Research
Published
2004-05
Volume
14
Issue
5
Pages
988-995
ISSN
1088-9051
Cited by
2,542
References
3
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