Cargando…
Unique insights from ClinicalTrials.gov by mining protein mutations and RSids in addition to applying the Human Phenotype Ontology
Researchers and clinicians face a significant challenge in keeping up-to-date with the rapid rate of new associations between genetic mutations and diseases. To remedy this problem, this research mined the ClinicalTrials.gov corpus to extract relevant biological insights, produce unique reports to s...
Autor principal: | Alag, Shray |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7252633/ https://www.ncbi.nlm.nih.gov/pubmed/32459809 http://dx.doi.org/10.1371/journal.pone.0233438 |
Ejemplares similares
-
Analysis of COVID-19 clinical trials: A data-driven, ontology-based, and natural language processing approach
por: Alag, Shray
Publicado: (2020) -
Systematic drug repositioning through mining adverse event data in ClinicalTrials.gov
por: Su, Eric Wen, et al.
Publicado: (2017) -
Some data quality issues at ClinicalTrials.gov
por: Chaturvedi, Neha, et al.
Publicado: (2019) -
Obstacles to the reuse of study metadata in ClinicalTrials.gov
por: Miron, Laura, et al.
Publicado: (2020) -
Registration of phase 3 crossover trials on ClinicalTrials.gov
por: Zeng, Lijuan, et al.
Publicado: (2020)