An association rule based model for information extraction from protein sequence data

In this paper, a data mining technique for protein sequence pattern extraction is developed. Specifically, the aim is to explore the use of association rules as a basis to build successful secondary structure predictors, in a sequencestructure layer. No heuristic or biological infor mation is taken...

Full description

Autores:
Becerra, David
Cantor Monroy, Giovanni Antonio
Niño, Luis Fernando
Gómez Perdomo, Jonatan
Bobadilla, Leonardo
Tipo de recurso:
Article of journal
Fecha de publicación:
2008
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/24338
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/24338
http://bdigital.unal.edu.co/15375/
Palabra clave:
Data Mining
Secondary Structure Prediction
Association Rules.
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
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spelling Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Becerra, David23121339-2173-42b4-9a92-83d0bf71136b300Cantor Monroy, Giovanni Antonioc5b2bd53-d0c5-48e6-8f5d-c47ed758d88e300Niño, Luis Fernando28761bdc-7a8d-4db3-8e8b-53d961086d72300Gómez Perdomo, Jonatan43ef4bd0-7b88-44b2-8a35-e49c549101e5300Bobadilla, Leonardo20035300-2499-40f2-b728-47d02d52a7603002019-06-25T22:36:05Z2019-06-25T22:36:05Z2008https://repositorio.unal.edu.co/handle/unal/24338http://bdigital.unal.edu.co/15375/In this paper, a data mining technique for protein sequence pattern extraction is developed. Specifically, the aim is to explore the use of association rules as a basis to build successful secondary structure predictors, in a sequencestructure layer. No heuristic or biological infor mation is taken into account in the present study and only the information given by the association rules is used as a basis for building a secondary structure predictor. This work gives some insights about secondary structure prediction features to be used in learning algorithms; this is expected to be useful to achieve substantial improvements of accuracy in protein secondary structure prediction.application/pdfspaUniversidad Nacional de Colombia -Sede Medellínhttp://revistas.unal.edu.co/index.php/avances/article/view/9980Universidad Nacional de Colombia Revistas electrónicas UN Avances en Sistemas e InformáticaAvances en Sistemas e InformáticaAvances en Sistemas e Informática; Vol. 5, núm. 1 (2008) Avances en Sistemas e Informática; Vol. 5, núm. 1 (2008) 1909-0056 1657-7663Becerra, David and Cantor Monroy, Giovanni Antonio and Niño, Luis Fernando and Gómez Perdomo, Jonatan and Bobadilla, Leonardo (2008) An association rule based model for information extraction from protein sequence data. Avances en Sistemas e Informática; Vol. 5, núm. 1 (2008) Avances en Sistemas e Informática; Vol. 5, núm. 1 (2008) 1909-0056 1657-7663 .An association rule based model for information extraction from protein sequence dataArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTData MiningSecondary Structure PredictionAssociation Rules.ORIGINAL9980-18056-1-PB.pdfapplication/pdf2778458https://repositorio.unal.edu.co/bitstream/unal/24338/1/9980-18056-1-PB.pdff26649ebc6d0ddf1f59fabf2c5e1034eMD51THUMBNAIL9980-18056-1-PB.pdf.jpg9980-18056-1-PB.pdf.jpgGenerated Thumbnailimage/jpeg9841https://repositorio.unal.edu.co/bitstream/unal/24338/2/9980-18056-1-PB.pdf.jpg0f522c9939f9df4706be05e62f911224MD52unal/24338oai:repositorio.unal.edu.co:unal/243382023-10-16 23:06:11.732Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co
dc.title.spa.fl_str_mv An association rule based model for information extraction from protein sequence data
title An association rule based model for information extraction from protein sequence data
spellingShingle An association rule based model for information extraction from protein sequence data
Data Mining
Secondary Structure Prediction
Association Rules.
title_short An association rule based model for information extraction from protein sequence data
title_full An association rule based model for information extraction from protein sequence data
title_fullStr An association rule based model for information extraction from protein sequence data
title_full_unstemmed An association rule based model for information extraction from protein sequence data
title_sort An association rule based model for information extraction from protein sequence data
dc.creator.fl_str_mv Becerra, David
Cantor Monroy, Giovanni Antonio
Niño, Luis Fernando
Gómez Perdomo, Jonatan
Bobadilla, Leonardo
dc.contributor.author.spa.fl_str_mv Becerra, David
Cantor Monroy, Giovanni Antonio
Niño, Luis Fernando
Gómez Perdomo, Jonatan
Bobadilla, Leonardo
dc.subject.proposal.spa.fl_str_mv Data Mining
Secondary Structure Prediction
Association Rules.
topic Data Mining
Secondary Structure Prediction
Association Rules.
description In this paper, a data mining technique for protein sequence pattern extraction is developed. Specifically, the aim is to explore the use of association rules as a basis to build successful secondary structure predictors, in a sequencestructure layer. No heuristic or biological infor mation is taken into account in the present study and only the information given by the association rules is used as a basis for building a secondary structure predictor. This work gives some insights about secondary structure prediction features to be used in learning algorithms; this is expected to be useful to achieve substantial improvements of accuracy in protein secondary structure prediction.
publishDate 2008
dc.date.issued.spa.fl_str_mv 2008
dc.date.accessioned.spa.fl_str_mv 2019-06-25T22:36:05Z
dc.date.available.spa.fl_str_mv 2019-06-25T22:36:05Z
dc.type.spa.fl_str_mv Artículo de revista
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format http://purl.org/coar/resource_type/c_6501
status_str publishedVersion
dc.identifier.uri.none.fl_str_mv https://repositorio.unal.edu.co/handle/unal/24338
dc.identifier.eprints.spa.fl_str_mv http://bdigital.unal.edu.co/15375/
url https://repositorio.unal.edu.co/handle/unal/24338
http://bdigital.unal.edu.co/15375/
dc.language.iso.spa.fl_str_mv spa
language spa
dc.relation.spa.fl_str_mv http://revistas.unal.edu.co/index.php/avances/article/view/9980
dc.relation.ispartof.spa.fl_str_mv Universidad Nacional de Colombia Revistas electrónicas UN Avances en Sistemas e Informática
Avances en Sistemas e Informática
dc.relation.ispartofseries.none.fl_str_mv Avances en Sistemas e Informática; Vol. 5, núm. 1 (2008) Avances en Sistemas e Informática; Vol. 5, núm. 1 (2008) 1909-0056 1657-7663
dc.relation.references.spa.fl_str_mv Becerra, David and Cantor Monroy, Giovanni Antonio and Niño, Luis Fernando and Gómez Perdomo, Jonatan and Bobadilla, Leonardo (2008) An association rule based model for information extraction from protein sequence data. Avances en Sistemas e Informática; Vol. 5, núm. 1 (2008) Avances en Sistemas e Informática; Vol. 5, núm. 1 (2008) 1909-0056 1657-7663 .
dc.rights.spa.fl_str_mv Derechos reservados - Universidad Nacional de Colombia
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.license.spa.fl_str_mv Atribución-NoComercial 4.0 Internacional
dc.rights.uri.spa.fl_str_mv http://creativecommons.org/licenses/by-nc/4.0/
dc.rights.accessrights.spa.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv Atribución-NoComercial 4.0 Internacional
Derechos reservados - Universidad Nacional de Colombia
http://creativecommons.org/licenses/by-nc/4.0/
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Universidad Nacional de Colombia -Sede Medellín
institution Universidad Nacional de Colombia
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repository.name.fl_str_mv Repositorio Institucional Universidad Nacional de Colombia
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