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RNAcode_Web - Convenient identification of evolutionary conserved protein coding regions.
Anders, John; Stadler, Peter F.
Afiliación
  • Anders J; Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, Universität Leipzig, Härtelstraße 16-18, D-04107 Leipzig, Germany.
  • Stadler PF; Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, Universität Leipzig, Härtelstraße 16-18, D-04107 Leipzig, Germany.
J Integr Bioinform ; 20(3)2023 Sep 01.
Article en En | MEDLINE | ID: mdl-37615674
ABSTRACT
The differentiation of regions with coding potential from non-coding regions remains a key task in computational biology. Methods such as RNAcode that exploit patterns of sequence conservation for this task have a substantial advantage in classification accuracy in particular for short coding sequences, compared to methods that rely on a single input sequence. However, they require sequence alignments as input. Frequently, suitable multiple sequence alignments are not readily available and are tedious, and sometimes difficult to construct. We therefore introduce here a new web service that provides access to the well-known coding sequence detector RNAcode with minimal user overhead. It requires as input only a single target nucleotide sequence. The service automates the collection, selection, and preparation of homologous sequences from the NCBI database, as well as the construction of the multiple sequence alignment that are needed as input for RNAcode. The service automatizes the entire pre- and postprocessing and thus makes the investigation of specific genomic regions for previously unannotated coding regions, such as small peptides or additional introns, a simple task that is easily accessible to non-expert users. RNAcode_Web is accessible online at rnacode.bioinf.uni-leipzig.de.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Programas Informáticos / Genómica Tipo de estudio: Diagnostic_studies Idioma: En Revista: J Integr Bioinform Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Programas Informáticos / Genómica Tipo de estudio: Diagnostic_studies Idioma: En Revista: J Integr Bioinform Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article