Cargando…
An annotated dataset for extracting gene-melanoma relations from scientific literature
BACKGROUND: Melanoma is one of the least common but the deadliest of skin cancers. This cancer begins when the genes of a cell suffer damage or fail, and identifying the genes involved in melanoma is crucial for understanding the melanoma tumorigenesis. Thousands of publications about human melanoma...
Autores principales: | Zanoli, Roberto, Lavelli, Alberto, Löffler, Theresa, Perez Gonzalez, Nicolas Andres, Rinaldi, Fabio |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8772125/ https://www.ncbi.nlm.nih.gov/pubmed/35045882 http://dx.doi.org/10.1186/s13326-021-00251-3 |
Ejemplares similares
-
A knowledge-poor approach to chemical-disease relation extraction
por: Alam, Firoj, et al.
Publicado: (2016) -
Determining similarity of scientific entities in annotation datasets
por: Palma, Guillermo, et al.
Publicado: (2015) -
Milk microfiltration process dataset annotated from a collection of scientific papers
por: Buche, Patrice, et al.
Publicado: (2021) -
Learning adaptive representations for entity recognition in the biomedical domain
por: Lauriola, Ivano, et al.
Publicado: (2021) -
Dataset of solution-based inorganic materials synthesis procedures extracted from the scientific literature
por: Wang, Zheren, et al.
Publicado: (2022)