Predicting Gene-Disease Associations with Knowledge Graph Embeddings over Multiple Ontologies
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10451/52109 |
Resumo: | Tese de mestrado, Bioinformática e Biologia Computacional, Universidade de Lisboa, Faculdade de Ciências, 2021 |
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Predicting Gene-Disease Associations with Knowledge Graph Embeddings over Multiple Ontologiesontologiassemelhança semânticagrafos de conhecimentorepresentações semânticasaprendizagem automáticaTeses de mestrado - 2021Departamento de InformáticaTese de mestrado, Bioinformática e Biologia Computacional, Universidade de Lisboa, Faculdade de Ciências, 2021There are still more than 1,400 Mendelian conditions whose molecular cause is un known. In addition, almost all medical conditions are somehow influenced by human genetic variation. This challenge also presents itself as an opportunity to understand the mechanisms of diseases, thus allowing the development of better mitigation strategies, finding diagnostic markers and therapeutic targets. Deciphering the link between genes and diseases is one of the most demanding tasks in biomedical research. Computational approaches for gene-disease associations prediction can greatly accelerate this process, and recent developments that explore the scientific knowledge described in ontologies have achieved good results. State-of-the-art approaches that take advantage of ontologies or knowledge graphs for these predictions are typically based on semantic similarity measures that only take into consideration hierarchical relations. New developments in the area of knowledge graphs embeddings support more powerful representations but are usually limited to a single ontology, which may be insufficient in multi-domain applications such as the prediction of gene-disease associations. This dissertation proposes a novel approach of gene-disease associations prediction by exploring both the Human Phenotype Ontology and the Gene Ontology, using knowledge graph embeddings to represent gene and disease features in a shared semantic space that covers both gene function and phenotypes. Our approach integrates different methods for building the shared semantic space, as well as multiple knowledge graph embeddings algorithms and machine learning methods. The prediction performance was evaluated on curated gene-disease associations from DisGeNET and compared to classical semantic similarity measures. Our experiments demonstrate the value of employing knowledge graph embeddings based on random walks and highlight the need for closer integration of different ontologies.Pesquita, Cátia, 1980-Repositório da Universidade de LisboaNunes, Susana Catarina Plácido2022-03-31T09:27:14Z202120212021-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10451/52109TID:202994287enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-08T16:57:11Zoai:repositorio.ul.pt:10451/52109Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:03:15.577329Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Predicting Gene-Disease Associations with Knowledge Graph Embeddings over Multiple Ontologies |
title |
Predicting Gene-Disease Associations with Knowledge Graph Embeddings over Multiple Ontologies |
spellingShingle |
Predicting Gene-Disease Associations with Knowledge Graph Embeddings over Multiple Ontologies Nunes, Susana Catarina Plácido ontologias semelhança semântica grafos de conhecimento representações semânticas aprendizagem automática Teses de mestrado - 2021 Departamento de Informática |
title_short |
Predicting Gene-Disease Associations with Knowledge Graph Embeddings over Multiple Ontologies |
title_full |
Predicting Gene-Disease Associations with Knowledge Graph Embeddings over Multiple Ontologies |
title_fullStr |
Predicting Gene-Disease Associations with Knowledge Graph Embeddings over Multiple Ontologies |
title_full_unstemmed |
Predicting Gene-Disease Associations with Knowledge Graph Embeddings over Multiple Ontologies |
title_sort |
Predicting Gene-Disease Associations with Knowledge Graph Embeddings over Multiple Ontologies |
author |
Nunes, Susana Catarina Plácido |
author_facet |
Nunes, Susana Catarina Plácido |
author_role |
author |
dc.contributor.none.fl_str_mv |
Pesquita, Cátia, 1980- Repositório da Universidade de Lisboa |
dc.contributor.author.fl_str_mv |
Nunes, Susana Catarina Plácido |
dc.subject.por.fl_str_mv |
ontologias semelhança semântica grafos de conhecimento representações semânticas aprendizagem automática Teses de mestrado - 2021 Departamento de Informática |
topic |
ontologias semelhança semântica grafos de conhecimento representações semânticas aprendizagem automática Teses de mestrado - 2021 Departamento de Informática |
description |
Tese de mestrado, Bioinformática e Biologia Computacional, Universidade de Lisboa, Faculdade de Ciências, 2021 |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021 2021 2021-01-01T00:00:00Z 2022-03-31T09:27:14Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10451/52109 TID:202994287 |
url |
http://hdl.handle.net/10451/52109 |
identifier_str_mv |
TID:202994287 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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