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

Επιστημονική δημοσίευση - Άρθρο Περιοδικού uoadl:3219178 45 Αναγνώσεις

Μονάδα:
Ερευνητικό υλικό ΕΚΠΑ
Τίτλος:
Darling: A Web Application for Detecting Disease-Related Biomedical Entity Associations with Literature Mining
Γλώσσες Τεκμηρίου:
Αγγλικά
Περίληψη:
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. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Έτος δημοσίευσης:
2022
Συγγραφείς:
Karatzas, E.
Baltoumas, F.A.
Kasionis, I.
Sanoudou, D.
Eliopoulos, A.G.
Theodosiou, T.
Iliopoulos, I.
Pavlopoulos, G.A.
Περιοδικό:
Ancient Biomolecules
Εκδότης:
MDPI
Τόμος:
12
Αριθμός / τεύχος:
4
Λέξεις-κλειδιά:
growth differentiation factor 15; protein, Article; bibliographic database; bioinformatics; book; cardiovascular disease; cytokine production; darling database; data integration; data mining; disease association; disease ontology; genetic risk; growth rate; intellectual impairment; medical terminology; Medline; obesity; online system; phenotype; Roberts syndrome; scientific literature; software, Data Mining; Phenotype; Proteins; PubMed; Software
Επίσημο URL (Εκδότης):
DOI:
10.3390/biom12040520
Το ψηφιακό υλικό του τεκμηρίου δεν είναι διαθέσιμο.