Cargando…
Building a large gene expression-cancer knowledge base with limited human annotations
Cancer prevention is one of the most pressing challenges that public health needs to face. In this regard, data-driven research is central to assist medical solutions targeting cancer. To fully harness the power of data-driven research, it is imperative to have well-organized machine-readable facts...
Autores principales: | Marchesin, Stefano, Menotti, Laura, Giachelle, Fabio, Silvello, Gianmaria, Alonso, Omar |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10533344/ https://www.ncbi.nlm.nih.gov/pubmed/37768281 http://dx.doi.org/10.1093/database/baad061 |
Ejemplares similares
-
MedTAG: a portable and customizable annotation tool for biomedical documents
por: Giachelle, Fabio, et al.
Publicado: (2021) -
TBGA: a large-scale Gene-Disease Association dataset for Biomedical Relation Extraction
por: Marchesin, Stefano, et al.
Publicado: (2022) -
Search, access, and explore life science nanopublications on the Web
por: Giachelle, Fabio, et al.
Publicado: (2021) -
Modelling digital health data: The ExaMode ontology for computational pathology
por: Menotti, Laura, et al.
Publicado: (2023) -
Empowering digital pathology applications through explainable knowledge extraction tools
por: Marchesin, Stefano, et al.
Publicado: (2022)