Mar 10, 2010

Prodigal: prokaryotic gene recognition and translation initiation site identification

BMC Bioinformatics
Doug HyattLoren Hauser

Abstract

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. 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. 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.

  • References20
  • Citations1808

References

Mentioned in this Paper

Pseudomonas aeruginosa (antigen)
Haemophilus influenzae
Meningitis, Haemophilus
Genome
Escherichia coli K12
Ncbi Taxonomy
Codon, Terminator
Archaea
Computer Programs and Programming
Codon, Initiator

Related Feeds

Archaeogenetics

Recent advances in genomic sequencing has led to the discovery of new strains of Archaea and shed light on their evolutionary history. Discover the latest research on Archaeogenetics here.