CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts
Brief Bioinform, v. 22, n. 3, p. 1–11, maio. 2021
Artículo
en Inglés
| Sec. Est. Saúde SP, SESSP-IBPROD, Sec. Est. Saúde SP
| ID: bud-4057
Biblioteca responsable:
BR78.1
ABSTRACT
Motivation Characterization of the coding sequences (CDSs) is an essential step in transcriptome annotation. Incorrect identification of CDSs can lead to the prediction of non-existent proteins that can eventually compromise knowledge if databases are populated with similar incorrect predictions made in different genomes. Also, the correct identification of CDSs is important for the characterization of the untranslated regions (UTRs), which are known to be important regulators of the mRNA translation process. Considering this, we present CodAn (Coding sequence Annotator), a new approach to predict confident CDS and UTR regions in full or partial transcriptome sequences in eukaryote species. Results Our analysis revealed that CodAn performs confident predictions on full-length and partial transcripts with the strand sense of the CDS known or unknown. The comparative analysis showed that CodAn presents better overall performance than other approaches, mainly when considering the correct identification of the full CDS (i.e. correct identification of the start and stop codons). In this sense, CodAn is the best tool to be used in projects involving transcriptomic data. Availability CodAn is freely available at https//github.com/pedronachtigall/CodAn.
Texto completo:
Disponible
Colección:
Bases de datos nacionales
/
Brasil
Base de datos:
Sec. Est. Saúde SP
/
SESSP-IBPROD
Tipo de estudio:
Estudio diagnóstico
/
Estudio pronóstico
/
Factores de riesgo
Idioma:
Inglés
Revista:
Brief Bioinform
Año:
2021
Tipo del documento:
Artículo