Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2003 Jul 1;31(13):3601-4.
doi: 10.1093/nar/gkg527.

GlimmerM, Exonomy and Unveil: three ab initio eukaryotic genefinders

William H Majoros  1 , Mihaela Pertea, Corina Antonescu, Steven L Salzberg
Affiliations

GlimmerM, Exonomy and Unveil: three ab initio eukaryotic genefinders

William H Majoros et al. Nucleic Acids Res. .

Abstract

We present three programs for ab initio gene prediction in eukaryotes: Exonomy, Unveil and GlimmerM. Exonomy is a 23-state Generalized Hidden Markov Model (GHMM), Unveil is a 283-state standard Hidden Markov Model (HMM) and GlimmerM is a previously-described genefinder which utilizes decision trees and Interpolated Markov Models (IMMs). All three are readily re-trainable for new organisms and have been found to perform well compared to other genefinders. Results are presented for Arabidopsis thaliana. Cases have been found where each of the genefinders outperforms each of the others, demonstrating the collective value of this ensemble of genefinders. These programs are all accessible through webservers at http://www.tigr.org/software.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Simplified structure of two Markov model genefinders: (A) Unveil and (B) Exonomy.
Figure 2
Figure 2
An example in which Exonomy produces the correct gene model.
Figure 3
Figure 3
An example in which Unveil produces the correct gene model (as does Genscan).
Figure 4
Figure 4
An example in which GlimmerM produces the correct gene model.
See this image and copyright information in PMC

References

    1. Das M., Burge,C.B., Park,E., Colinas,J. and Pellitier,J. (2001) Assessment of the total number of human transcription units. Genomics, 77, 71–78. - PubMed
    1. Guigo R., Dermitzakis,E.T., Agarwal,P., Ponting,C.P., Parra,G., Reymond,A., Abril,J.F., Keibler,E., Lyle,R., Ucla,C., Antonarakis,S.T. and Brent,M.R. (2003) Comparison of mouse and human genomes followed by experimental verification yields an estimated 1019 additional genes. Proc. Natl Acad. Sci. USA, 100, 1140–1145. - PMC - PubMed
    1. Salzberg S.L., Delcher,A.L., Kasif,S. and White,O. (1998) Microbial gene identification using interpolated Markov models. Nucleic Acids Res., 26, 544–548. - PMC - PubMed
    1. Salzberg S.L., Searls,D.B. and Kasif,S. (eds). (1998) Computational Methods in Molecular Biology. Elsevier, Amsterdam, The Netherlands.
    1. Durbin R., Eddy,S., Krogh,A. and Mitchison,G. (1998) Biological Sequence Analysis. Cambridge University Press, Cambridge, UK.

Publication types