Abstract
Background: The quality of automated gene prediction in microbial organisms has improved steadily over the past decade, but there is still room for improvement. Increasing the number of correct identifications, both of genes and of the translation initiation sites for each gene, and reducing the overall number of false positives, are all desirable goals.Results: With our years of experience in manually curating genomes for the Joint Genome Institute, we developed a new gene prediction algorithm called Prodigal (PROkaryotic DYnamic programming Gene-finding ALgorithm). With Prodigal, we focused specifically on the three goals of improved gene structure prediction, improved translation initiation site recognition, and reduced false positives. We compared the results of Prodigal to existing gene-finding methods to demonstrate that it met each of these objectives.Conclusion: We built a fast, lightweight, open source gene prediction program called Prodigal http://compbio.ornl.gov/prodigal/. Prodigal achieved good results compared to existing methods, and we believe it will be a valuable asset to automated microbial annotation pipelines.
| Original language | English |
|---|---|
| Article number | 119 |
| Journal | BMC Bioinformatics |
| Volume | 11 |
| DOIs | |
| State | Published - Mar 8 2010 |
Funding
The authors wish to acknowledge Robert W. Cottingham, Edward C. Uberbacher, Cynthia Jeffries, and Yun-Juan Chang for helpful discussions and suggestions. The authors also wish to acknowledge Mark Borodovsky for helpful discussions and the provision of the Genemark software. Support for this research was provided by the U.S. Department of Energy, Office of Science, Biological and Environmental Research Programs. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the U.S. Department of Energy under contract DE-AC05-00OR22725.
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