CapsProm : a capsule network for promoter prediction.

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.creatorMoraes, Lauro Ângelo Gonçalves de-
Autor(es): dc.creatorSilva, Pedro Henrique Lopes-
Autor(es): dc.creatorLuz, Eduardo José da Silva-
Autor(es): dc.creatorMoreira, Gladston Juliano Prates-
Data de aceite: dc.date.accessioned2025-08-21T15:37:33Z-
Data de disponibilização: dc.date.available2025-08-21T15:37:33Z-
Data de envio: dc.date.issued2023-07-24-
Data de envio: dc.date.issued2023-07-24-
Data de envio: dc.date.issued2021-
Fonte completa do material: dc.identifierhttp://www.repositorio.ufop.br/jspui/handle/123456789/17035-
Fonte completa do material: dc.identifierhttps://www.sciencedirect.com/science/article/pii/S001048252200419X-
Fonte completa do material: dc.identifierhttps://doi.org/10.1016/j.compbiomed.2022.105627-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1020052-
Descrição: dc.descriptionLocating the promoter region in DNA sequences is of paramount importance in bioinformatics. This problem has been widely studied in the literature, but it has not yet been fully resolved. Some researchers have shown remarkable results using convolutional networks that allowed the automatic extraction of features from a DNA chain. However, a single architecture schema that could learn the promoter prediction task competitively for several organisms has not yet been achieved. Thus, researchers must seek new architectures by hand-designing or by Neural Architecture Search for each new evaluated organism dataset. This work proposes a versatile archi- tecture based on a capsule network that can accurately identify promoter sequences in raw DNA data from five different organisms, eukaryotic and prokaryotic. Our architecture, the CapsProm, could help create models with minimum effort to learn the promoter identification task between different datasets. Furthermore, the CapsProm showed competitive results, overcoming the baseline method in five out of seven tested datasets (F1-score). The models and source code are made available at https://github.com/lauromoraes/CapsNet-promoter.-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Direitos: dc.rightsrestrito-
Palavras-chave: dc.subjectDeep learning-
Palavras-chave: dc.subjectGenomics-
Título: dc.titleCapsProm : a capsule network for promoter prediction.-
Aparece nas coleções:Repositório Institucional - UFOP

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