Deep neural architectures for highly imbalanced data in bioinformatics

Autores
Bugnon, Leandro A.; Yones, Cristian; Milone, Diego H.; Stegmayer, Georgina
Año de publicación
2019
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
In this work, we present two new variants to the deepSOM model: the deep elastic SOM (deSOM) and the deep ensemble elastic SOM (deeSOM), which overcome the mentioned issues. In deSOM the number of deep levels not only grows automatically, but also the size of each layer is expanded adaptively according to the data at each level, thus pre-miRNA neurons can be re-organized in a larger space.
Extended abstract from Deep neural architectures for highly imbalanced data in bioinformatics, L. A. Bugnon, C. Yones, D. H. Milone, G. Stegmayer, (to appear in) IEEE Transactions on Neural Networks and Learning Systems (2019), doi 10.1109/TNNLS.2019.2914471
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Bioinformatics
Pre-miRNA classification
Deep neural architectures
High class imbalance
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/87801
Acceder
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network_acronym_str SEDICI
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network_name_str SEDICI (UNLP)
spelling Deep neural architectures for highly imbalanced data in bioinformaticsBugnon, Leandro A.Yones, CristianMilone, Diego H.Stegmayer, GeorginaCiencias InformáticasBioinformaticsPre-miRNA classificationDeep neural architecturesHigh class imbalanceIn this work, we present two new variants to the deepSOM model: the deep elastic SOM (deSOM) and the deep ensemble elastic SOM (deeSOM), which overcome the mentioned issues. In deSOM the number of deep levels not only grows automatically, but also the size of each layer is expanded adaptively according to the data at each level, thus pre-miRNA neurons can be re-organized in a larger space.Extended abstract from Deep neural architectures for highly imbalanced data in bioinformatics, L. A. Bugnon, C. Yones, D. H. Milone, G. Stegmayer, (to appear in) IEEE Transactions on Neural Networks and Learning Systems (2019), doi 10.1109/TNNLS.2019.2914471Sociedad Argentina de Informática e Investigación Operativa2019-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionResumenhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf1-4http://sedici.unlp.edu.ar/handle/10915/87801enginfo:eu-repo/semantics/altIdentifier/issn/2683-8966info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/3.0/Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:17:29Zoai:sedici.unlp.edu.ar:10915/87801Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:17:29.812SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Deep neural architectures for highly imbalanced data in bioinformatics
title Deep neural architectures for highly imbalanced data in bioinformatics
spellingShingle Deep neural architectures for highly imbalanced data in bioinformatics
Bugnon, Leandro A.
Ciencias Informáticas
Bioinformatics
Pre-miRNA classification
Deep neural architectures
High class imbalance
title_short Deep neural architectures for highly imbalanced data in bioinformatics
title_full Deep neural architectures for highly imbalanced data in bioinformatics
title_fullStr Deep neural architectures for highly imbalanced data in bioinformatics
title_full_unstemmed Deep neural architectures for highly imbalanced data in bioinformatics
title_sort Deep neural architectures for highly imbalanced data in bioinformatics
dc.creator.none.fl_str_mv Bugnon, Leandro A.
Yones, Cristian
Milone, Diego H.
Stegmayer, Georgina
author Bugnon, Leandro A.
author_facet Bugnon, Leandro A.
Yones, Cristian
Milone, Diego H.
Stegmayer, Georgina
author_role author
author2 Yones, Cristian
Milone, Diego H.
Stegmayer, Georgina
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Bioinformatics
Pre-miRNA classification
Deep neural architectures
High class imbalance
topic Ciencias Informáticas
Bioinformatics
Pre-miRNA classification
Deep neural architectures
High class imbalance
dc.description.none.fl_txt_mv In this work, we present two new variants to the deepSOM model: the deep elastic SOM (deSOM) and the deep ensemble elastic SOM (deeSOM), which overcome the mentioned issues. In deSOM the number of deep levels not only grows automatically, but also the size of each layer is expanded adaptively according to the data at each level, thus pre-miRNA neurons can be re-organized in a larger space.
Extended abstract from Deep neural architectures for highly imbalanced data in bioinformatics, L. A. Bugnon, C. Yones, D. H. Milone, G. Stegmayer, (to appear in) IEEE Transactions on Neural Networks and Learning Systems (2019), doi 10.1109/TNNLS.2019.2914471
Sociedad Argentina de Informática e Investigación Operativa
description In this work, we present two new variants to the deepSOM model: the deep elastic SOM (deSOM) and the deep ensemble elastic SOM (deeSOM), which overcome the mentioned issues. In deSOM the number of deep levels not only grows automatically, but also the size of each layer is expanded adaptively according to the data at each level, thus pre-miRNA neurons can be re-organized in a larger space.
publishDate 2019
dc.date.none.fl_str_mv 2019-09
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Resumen
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/87801
url http://sedici.unlp.edu.ar/handle/10915/87801
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/2683-8966
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/3.0/
Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/3.0/
Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)
dc.format.none.fl_str_mv application/pdf
1-4
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
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collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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