Gene prediction with a hidden Markov model and a new intron submodel (original) (raw)
Journal Article
,
Search for other works by this author on:
Search for other works by this author on:
Published:
27 September 2003
Navbar Search Filter Mobile Enter search term Search
Abstract
Motivation: The problem of finding the genes in eukaryotic DNA sequences by computational methods is still not satisfactorily solved. Gene finding programs have achieved relatively high accuracy on short genomic sequences but do not perform well on longer sequences with an unknown number of genes in them. Here existing programs tend to predict many false exons.
Results: We have developed a new program, AUGUSTUS, for the ab initio prediction of protein coding genes in eukaryotic genomes. The program is based on a Hidden Markov Model and integrates a number of known methods and submodels. It employs a new way of modeling intron lengths. We use a new donor splice site model, a new model for a short region directly upstream of the donor splice site model that takes the reading frame into account and apply a method that allows better GC-content dependent parameter estimation. AUGUSTUS predicts on longer sequences far more human and drosophila genes accurately than the ab initio gene prediction programs we compared it with, while at the same time being more specific.
Availability: A web interface for AUGUSTUS and the executable program are located at http://augustus.gobics.de.
Supplementary Information: The datasets used for testing and training are available at http://augustus.gobics.de/datasets/
Contact: mstanke@gwdg.de
*
To whom correspondence should be addressed.
© Oxford University Press 2003
Citations
Views
Altmetric
Metrics
Total Views 6,833
3,033 Pageviews
3,800 PDF Downloads
Since 11/1/2016
Month: | Total Views: |
---|---|
November 2016 | 9 |
December 2016 | 9 |
January 2017 | 30 |
February 2017 | 86 |
March 2017 | 98 |
April 2017 | 63 |
May 2017 | 75 |
June 2017 | 40 |
July 2017 | 52 |
August 2017 | 41 |
September 2017 | 26 |
October 2017 | 50 |
November 2017 | 52 |
December 2017 | 194 |
January 2018 | 151 |
February 2018 | 137 |
March 2018 | 144 |
April 2018 | 179 |
May 2018 | 53 |
June 2018 | 56 |
July 2018 | 38 |
August 2018 | 31 |
September 2018 | 29 |
October 2018 | 32 |
November 2018 | 65 |
December 2018 | 34 |
January 2019 | 29 |
February 2019 | 34 |
March 2019 | 55 |
April 2019 | 61 |
May 2019 | 41 |
June 2019 | 83 |
July 2019 | 59 |
August 2019 | 62 |
September 2019 | 49 |
October 2019 | 79 |
November 2019 | 68 |
December 2019 | 68 |
January 2020 | 62 |
February 2020 | 41 |
March 2020 | 50 |
April 2020 | 69 |
May 2020 | 41 |
June 2020 | 91 |
July 2020 | 31 |
August 2020 | 54 |
September 2020 | 52 |
October 2020 | 56 |
November 2020 | 88 |
December 2020 | 95 |
January 2021 | 61 |
February 2021 | 55 |
March 2021 | 79 |
April 2021 | 68 |
May 2021 | 76 |
June 2021 | 115 |
July 2021 | 50 |
August 2021 | 50 |
September 2021 | 73 |
October 2021 | 61 |
November 2021 | 63 |
December 2021 | 49 |
January 2022 | 52 |
February 2022 | 58 |
March 2022 | 81 |
April 2022 | 81 |
May 2022 | 79 |
June 2022 | 115 |
July 2022 | 58 |
August 2022 | 37 |
September 2022 | 75 |
October 2022 | 92 |
November 2022 | 65 |
December 2022 | 53 |
January 2023 | 70 |
February 2023 | 125 |
March 2023 | 153 |
April 2023 | 125 |
May 2023 | 92 |
June 2023 | 84 |
July 2023 | 41 |
August 2023 | 50 |
September 2023 | 53 |
October 2023 | 75 |
November 2023 | 69 |
December 2023 | 87 |
January 2024 | 127 |
February 2024 | 97 |
March 2024 | 216 |
April 2024 | 101 |
May 2024 | 89 |
June 2024 | 69 |
July 2024 | 71 |
August 2024 | 59 |
September 2024 | 74 |
October 2024 | 68 |
×
Email alerts
Citing articles via
More from Oxford Academic