Thalia: Semantic search engine for biomedical abstracts

Autores
Soto, Axel Juan; Przybyla, Piotr; Ananiadou, Sophia
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
While publication rate of the biomedical literature has been growing steadily during the last decades, the accessibility of pertinent research publications for biologist and medical practitioners remains a challenge. This paper describes Thalia, which is a semantic search engine that can recognize eight different types of concepts occurring in biomedical abstracts. Thalia is available via a web-based interface or a RESTful API. A key aspect of our search engine is that it is updated from PubMed on a daily basis. We describe here the main building blocks of our tool as well as an evaluation of the retrieval capabilities of Thalia in the context of a precision medicine dataset.
Fil: Soto, Axel Juan. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. University of Manchester; Reino Unido
Fil: Przybyla, Piotr. University of Manchester; Reino Unido
Fil: Ananiadou, Sophia. University of Manchester; Reino Unido
Materia
RESTFUL API
THALIA
SEMANTIC SEARCH ENGINE
PRECISION MEDICINE DATASET
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/90965
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/90965
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Thalia: Semantic search engine for biomedical abstractsSoto, Axel JuanPrzybyla, PiotrAnaniadou, SophiaRESTFUL APITHALIASEMANTIC SEARCH ENGINEPRECISION MEDICINE DATASEThttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1While publication rate of the biomedical literature has been growing steadily during the last decades, the accessibility of pertinent research publications for biologist and medical practitioners remains a challenge. This paper describes Thalia, which is a semantic search engine that can recognize eight different types of concepts occurring in biomedical abstracts. Thalia is available via a web-based interface or a RESTful API. A key aspect of our search engine is that it is updated from PubMed on a daily basis. We describe here the main building blocks of our tool as well as an evaluation of the retrieval capabilities of Thalia in the context of a precision medicine dataset.Fil: Soto, Axel Juan. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. University of Manchester; Reino UnidoFil: Przybyla, Piotr. University of Manchester; Reino UnidoFil: Ananiadou, Sophia. University of Manchester; Reino UnidoOxford University Press2018-05-15info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/90965Soto, Axel Juan; Przybyla, Piotr; Ananiadou, Sophia; Thalia: Semantic search engine for biomedical abstracts; Oxford University Press; Bioinformatics (Oxford, England); 35; 10; 15-5-2018; 1799-18011367-4803CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/bty871/5134063info:eu-repo/semantics/altIdentifier/doi/10.1093/bioinformatics/bty871info:eu-repo/semantics/altIdentifier/url/https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6513154/info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-11-05T09:56:41Zoai:ri.conicet.gov.ar:11336/90965instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-11-05 09:56:41.915CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Thalia: Semantic search engine for biomedical abstracts
title Thalia: Semantic search engine for biomedical abstracts
spellingShingle Thalia: Semantic search engine for biomedical abstracts
Soto, Axel Juan
RESTFUL API
THALIA
SEMANTIC SEARCH ENGINE
PRECISION MEDICINE DATASET
title_short Thalia: Semantic search engine for biomedical abstracts
title_full Thalia: Semantic search engine for biomedical abstracts
title_fullStr Thalia: Semantic search engine for biomedical abstracts
title_full_unstemmed Thalia: Semantic search engine for biomedical abstracts
title_sort Thalia: Semantic search engine for biomedical abstracts
dc.creator.none.fl_str_mv Soto, Axel Juan
Przybyla, Piotr
Ananiadou, Sophia
author Soto, Axel Juan
author_facet Soto, Axel Juan
Przybyla, Piotr
Ananiadou, Sophia
author_role author
author2 Przybyla, Piotr
Ananiadou, Sophia
author2_role author
author
dc.subject.none.fl_str_mv RESTFUL API
THALIA
SEMANTIC SEARCH ENGINE
PRECISION MEDICINE DATASET
topic RESTFUL API
THALIA
SEMANTIC SEARCH ENGINE
PRECISION MEDICINE DATASET
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv While publication rate of the biomedical literature has been growing steadily during the last decades, the accessibility of pertinent research publications for biologist and medical practitioners remains a challenge. This paper describes Thalia, which is a semantic search engine that can recognize eight different types of concepts occurring in biomedical abstracts. Thalia is available via a web-based interface or a RESTful API. A key aspect of our search engine is that it is updated from PubMed on a daily basis. We describe here the main building blocks of our tool as well as an evaluation of the retrieval capabilities of Thalia in the context of a precision medicine dataset.
Fil: Soto, Axel Juan. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. University of Manchester; Reino Unido
Fil: Przybyla, Piotr. University of Manchester; Reino Unido
Fil: Ananiadou, Sophia. University of Manchester; Reino Unido
description While publication rate of the biomedical literature has been growing steadily during the last decades, the accessibility of pertinent research publications for biologist and medical practitioners remains a challenge. This paper describes Thalia, which is a semantic search engine that can recognize eight different types of concepts occurring in biomedical abstracts. Thalia is available via a web-based interface or a RESTful API. A key aspect of our search engine is that it is updated from PubMed on a daily basis. We describe here the main building blocks of our tool as well as an evaluation of the retrieval capabilities of Thalia in the context of a precision medicine dataset.
publishDate 2018
dc.date.none.fl_str_mv 2018-05-15
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/90965
Soto, Axel Juan; Przybyla, Piotr; Ananiadou, Sophia; Thalia: Semantic search engine for biomedical abstracts; Oxford University Press; Bioinformatics (Oxford, England); 35; 10; 15-5-2018; 1799-1801
1367-4803
CONICET Digital
CONICET
url http://hdl.handle.net/11336/90965
identifier_str_mv Soto, Axel Juan; Przybyla, Piotr; Ananiadou, Sophia; Thalia: Semantic search engine for biomedical abstracts; Oxford University Press; Bioinformatics (Oxford, England); 35; 10; 15-5-2018; 1799-1801
1367-4803
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/bty871/5134063
info:eu-repo/semantics/altIdentifier/doi/10.1093/bioinformatics/bty871
info:eu-repo/semantics/altIdentifier/url/https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6513154/
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Oxford University Press
publisher.none.fl_str_mv Oxford University Press
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1847977355329404928
score 13.087074

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