RegEl corpus: identifying DNA regulatory elements in the scientific literature.
Database (Oxford)
; 20222022 06 27.
Article
em En
| MEDLINE
| ID: mdl-35758881
ABSTRACT
High-throughput technologies led to the generation of a wealth of data on regulatory DNA elements in the human genome. However, results from disease-driven studies are primarily shared in textual form as scientific articles. Information extraction (IE) algorithms allow this information to be (semi-)automatically accessed. Their development, however, is dependent on the availability of annotated corpora. Therefore, we introduce RegEl (Regulatory Elements), the first freely available corpus annotated with regulatory DNA elements comprising 305 PubMed abstracts for a total of 2690 sentences. We focus on enhancers, promoters and transcription factor binding sites. Three annotators worked in two stages, achieving an overall 0.73 F1 inter-annotator agreement and 0.46 for regulatory elements. Depending on the entity type, IE baselines reach F1-scores of 0.48-0.91 for entity detection and 0.71-0.88 for entity normalization. Next, we apply our entity detection models to the entire PubMed collection and extract co-occurrences of genes or diseases with regulatory elements. This generates large collections of regulatory elements associated with 137 870 unique genes and 7420 diseases, which we make openly available. Database URL https//zenodo.org/record/6418451#.YqcLHvexVqg.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Mineração de Dados
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Database (Oxford)
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Alemanha