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Balrog: A universal protein model for prokaryotic gene prediction.
Sommer, Markus J; Salzberg, Steven L.
Afiliación
  • Sommer MJ; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.
  • Salzberg SL; Center for Computational Biology, Johns Hopkins University, Baltimore, Maryland, United States of America.
PLoS Comput Biol ; 17(2): e1008727, 2021 02.
Article en En | MEDLINE | ID: mdl-33635857
Low-cost, high-throughput sequencing has led to an enormous increase in the number of sequenced microbial genomes, with well over 100,000 genomes in public archives today. Automatic genome annotation tools are integral to understanding these organisms, yet older gene finding methods must be retrained on each new genome. We have developed a universal model of prokaryotic genes by fitting a temporal convolutional network to amino-acid sequences from a large, diverse set of microbial genomes. We incorporated the new model into a gene finding system, Balrog (Bacterial Annotation by Learned Representation Of Genes), which does not require genome-specific training and which matches or outperforms other state-of-the-art gene finding tools. Balrog is freely available under the MIT license at https://github.com/salzberg-lab/Balrog.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Células Procariotas / Genoma Bacteriano / Perfilación de la Expresión Génica / Genómica / Genoma Microbiano Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Células Procariotas / Genoma Bacteriano / Perfilación de la Expresión Génica / Genómica / Genoma Microbiano Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos