Mining the biomedical literature to predict shared drug targets in drugbank

Autores
Caniza, Horacio; Galeano, Diego; Paccanaro, Alberto
Año de publicación
2017
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
The current drug development pipelines are characterised by long processes with high attrition rates and elevated costs. More than 80% of new compounds fail in the later stages of testing due to severe side-effects caused by unknown biomolecular targets of the compounds. In this work, we present a measure that can predict shared targets for drugs in DrugBank through large scale analysis of the biomedical literature. We show that using MeSH ontology terms can accurately describe the drugs and that appropriate use of the MeSH ontological structure can determine pairwise drug similarity.
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
Materia
Ciencias Informáticas
MeSH terms
drug descriptors
drug targets
drugbank
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-sa/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/63201
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/63201
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Mining the biomedical literature to predict shared drug targets in drugbankCaniza, HoracioGaleano, DiegoPaccanaro, AlbertoCiencias InformáticasMeSH termsdrug descriptorsdrug targetsdrugbankThe current drug development pipelines are characterised by long processes with high attrition rates and elevated costs. More than 80% of new compounds fail in the later stages of testing due to severe side-effects caused by unknown biomolecular targets of the compounds. In this work, we present a measure that can predict shared targets for drugs in DrugBank through large scale analysis of the biomedical literature. We show that using MeSH ontology terms can accurately describe the drugs and that appropriate use of the MeSH ontological structure can determine pairwise drug similarity.Sociedad Argentina de Informática e Investigación Operativa (SADIO)2017-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/63201enginfo:eu-repo/semantics/altIdentifier/url/http://www.clei2017-46jaiio.sadio.org.ar/sites/default/files/Mem/SLMDI/SLMDI-03.pdfinfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-sa/3.0/Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T11:00:47Zoai:sedici.unlp.edu.ar:10915/63201Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 11:00:48.197SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Mining the biomedical literature to predict shared drug targets in drugbank
title Mining the biomedical literature to predict shared drug targets in drugbank
spellingShingle Mining the biomedical literature to predict shared drug targets in drugbank
Caniza, Horacio
Ciencias Informáticas
MeSH terms
drug descriptors
drug targets
drugbank
title_short Mining the biomedical literature to predict shared drug targets in drugbank
title_full Mining the biomedical literature to predict shared drug targets in drugbank
title_fullStr Mining the biomedical literature to predict shared drug targets in drugbank
title_full_unstemmed Mining the biomedical literature to predict shared drug targets in drugbank
title_sort Mining the biomedical literature to predict shared drug targets in drugbank
dc.creator.none.fl_str_mv Caniza, Horacio
Galeano, Diego
Paccanaro, Alberto
author Caniza, Horacio
author_facet Caniza, Horacio
Galeano, Diego
Paccanaro, Alberto
author_role author
author2 Galeano, Diego
Paccanaro, Alberto
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
MeSH terms
drug descriptors
drug targets
drugbank
topic Ciencias Informáticas
MeSH terms
drug descriptors
drug targets
drugbank
dc.description.none.fl_txt_mv The current drug development pipelines are characterised by long processes with high attrition rates and elevated costs. More than 80% of new compounds fail in the later stages of testing due to severe side-effects caused by unknown biomolecular targets of the compounds. In this work, we present a measure that can predict shared targets for drugs in DrugBank through large scale analysis of the biomedical literature. We show that using MeSH ontology terms can accurately describe the drugs and that appropriate use of the MeSH ontological structure can determine pairwise drug similarity.
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
description The current drug development pipelines are characterised by long processes with high attrition rates and elevated costs. More than 80% of new compounds fail in the later stages of testing due to severe side-effects caused by unknown biomolecular targets of the compounds. In this work, we present a measure that can predict shared targets for drugs in DrugBank through large scale analysis of the biomedical literature. We show that using MeSH ontology terms can accurately describe the drugs and that appropriate use of the MeSH ontological structure can determine pairwise drug similarity.
publishDate 2017
dc.date.none.fl_str_mv 2017-09
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
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/10915/63201
url http://sedici.unlp.edu.ar/handle/10915/63201
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.clei2017-46jaiio.sadio.org.ar/sites/default/files/Mem/SLMDI/SLMDI-03.pdf
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-sa/3.0/
Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-sa/3.0/
Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
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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score 13.22299

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