A modified GC-specific MAKER gene annotation method reveals improved and novel gene predictions of high and low GC content in Oryza sativa

BACKGROUND: Accurate structural annotation depends on well-trained gene prediction programs. Training data for gene prediction programs are often chosen randomly from a subset of high-quality genes that ideally represent the variation found within a genome. One aspect of gene variation is GC content...

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Detalles Bibliográficos
Autores principales: Bowman, Megan J., Pulman, Jane A., Liu, Tiffany L., Childs, Kevin L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5702205/
https://www.ncbi.nlm.nih.gov/pubmed/29178822
http://dx.doi.org/10.1186/s12859-017-1942-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5702205/
https://www.ncbi.nlm.nih.gov/pubmed/29178822
http://dx.doi.org/10.1186/s12859-017-1942-z

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