Eukaryotic Gene Prediction Using GeneMark.hmm‐E and GeneMark‐ES
互联网
- Abstract
- Table of Contents
- Figures
- Literature Cited
Abstract
This unit describes how to use the gene?finding programs GeneMark.hmm?E and GeneMark?ES for finding protein?coding genes in the genomic DNA of eukaryotic organisms. These bioinformatics tools have been demonstrated to have state?of?the?art accuracy for many fungal, plant, and animal genomes, and have frequently been used for gene annotation in novel genomic sequences. An additional advantage of GeneMark?ES is that the problem of algorithm parameterization is solved automatically, with parameters estimated by iterative self?training (unsupervised training). Curr. Protoc. Bioinform. 35:4.6.1?4.6.10. © 2011 by John Wiley & Sons, Inc.
Keywords: gene finding; hidden Markov model; unsupervised parameter estimation
Table of Contents
- Introduction
- Basic Protocol 1: Using GeneMark.hmm for Eukaryotic Gene Prediction via Web Interface
- Alternate Protocol 1: Using the Unix Version of GeneMark.hmm‐E
- Basic Protocol 2: Using GeneMark‐ES for Eukaryotic Gene Prediction
- Guidelines for Understanding Results
- Commentary
- Literature Cited
- Figures
Materials
Figures
-
Figure 4.6.1 The user interface for the eukaryotic GeneMark.hmm program. Required input includes a DNA sequence in FASTA format, either copied and pasted into the Sequence text box, or uploaded from one's local drive using the Browse button next to the Sequence File Upload box. View Image -
Figure 4.6.2 The text output for the Eukaryotic GeneMark.hmm program. View Image -
Figure 4.6.3 The graphical output from the Eukaryotic GeneMark.hmm program for a region of the example sequence. The six different panels represent the six possible reading frames, three each on the direct and reverse strands. View Image
Videos
Literature Cited
| Altschul, S.F., Gish, W., Miller, W., Myers, E.W., and Lipman, D.J. 1990. Basic local alignment search tool. J. Mol. Biol. 215:403‐410. | |
| Borodovsky, M. and McIninch, J. 1993. GeneMark: Parallel gene recognition for both DNA strands. Comput. Chem. 17:123‐133. | |
| Lukashin, A.V. and Borodovsky, M. 1998. GeneMark.hmm: New solutions for gene finding. Nucleic Acids Res. 26:1107hyphen;1115. | |
| Lomsadze, A., Ter‐Hovhannisyan, V., Chernoff, Y., and Borodovsky, M. 2005. Gene identification in novel eukaryotic genomes by self‐training algorithm. Nucleic Acids Res. 33:6494‐6506. | |
| Rabiner, L.R. 1989. A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the I.E.E.E. 77:257‐286. | |
| Ter‐Hovhannisyan, V., Lomsadze, A., Chernoff, Y., and Borodovsky, M. 2008. Gene prediction in novel fungal genomes using an ab initio algorithm with unsupervised training. Genome Res. 18:1979‐1990. | |
| Internet Resources | |
| http://topaz.gatech.edu/GeneMark | |
| GeneMark Web site. |
