Darling: A Web Application for Detecting Disease-Related Biomedical Entity Associations with Literature Mining

Finding, exploring and filtering frequent sentence-based associations between a disease and a biomedical entity, co-mentioned in disease-related PubMed literature, is a challenge, as the volume of publications increases. Darling is a web application, which utilizes Name Entity Recognition to identif...

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Detalles Bibliográficos
Autores principales: Karatzas, Evangelos, Baltoumas, Fotis A., Kasionis, Ioannis, Sanoudou, Despina, Eliopoulos, Aristides G., Theodosiou, Theodosios, Iliopoulos, Ioannis, Pavlopoulos, Georgios A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9028073/
https://www.ncbi.nlm.nih.gov/pubmed/35454109
http://dx.doi.org/10.3390/biom12040520
Descripción
Sumario:Finding, exploring and filtering frequent sentence-based associations between a disease and a biomedical entity, co-mentioned in disease-related PubMed literature, is a challenge, as the volume of publications increases. Darling is a web application, which utilizes Name Entity Recognition to identify human-related biomedical terms in PubMed articles, mentioned in OMIM, DisGeNET and Human Phenotype Ontology (HPO) disease records, and generates an interactive biomedical entity association network. Nodes in this network represent genes, proteins, chemicals, functions, tissues, diseases, environments and phenotypes. Users can search by identifiers, terms/entities or free text and explore the relevant abstracts in an annotated format.

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