bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-119

Preview meta tags from the bmcbioinformatics.biomedcentral.com website.

Linked Hostnames

22

Thumbnail

Search Engine Appearance

Google

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-119

Prodigal: prokaryotic gene recognition and translation initiation site identification - BMC Bioinformatics

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.



Bing

Prodigal: prokaryotic gene recognition and translation initiation site identification - BMC Bioinformatics

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-119

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.



DuckDuckGo

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-119

Prodigal: prokaryotic gene recognition and translation initiation site identification - BMC Bioinformatics

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.

  • General Meta Tags

    104
    • title
      Prodigal: prokaryotic gene recognition and translation initiation site identification | BMC Bioinformatics | Full Text
    • charset
      UTF-8
    • X-UA-Compatible
      IE=edge
    • applicable-device
      pc,mobile
    • viewport
      width=device-width, initial-scale=1
  • Open Graph Meta Tags

    6
    • og:url
      https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-119
    • og:type
      article
    • og:site_name
      BioMed Central
    • og:title
      Prodigal: prokaryotic gene recognition and translation initiation site identification - BMC Bioinformatics
    • og:description
      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.
  • Link Tags

    12
    • apple-touch-icon
      /static/img/favicons/bmc/apple-touch-icon-582ef1d0f5.png
    • canonical
      https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-119
    • icon
      /static/img/favicons/bmc/android-chrome-192x192-9625b7cdba.png
    • icon
      /static/img/favicons/bmc/favicon-32x32-5d7879efe1.png
    • icon
      /static/img/favicons/bmc/favicon-16x16-c241ac1a2f.png

Emails

2

Links

170