Cargando…
Assessing the druggability of protein-protein interactions by a supervised machine-learning method
BACKGROUND: Protein-protein interactions (PPIs) are challenging but attractive targets of small molecule drugs for therapeutic interventions of human diseases. In this era of rapid accumulation of PPI data, there is great need for a methodology that can efficiently select drug target PPIs by holisti...
Autores principales: | Sugaya, Nobuyoshi, Ikeda, Kazuyoshi |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2009
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2739204/ https://www.ncbi.nlm.nih.gov/pubmed/19703312 http://dx.doi.org/10.1186/1471-2105-10-263 |
Ejemplares similares
-
Dr. PIAS: an integrative system for assessing the druggability of protein-protein interactions
por: Sugaya, Nobuyoshi, et al.
Publicado: (2011) -
Dr. PIAS 2.0: an update of a database of predicted druggable protein–protein interactions
por: Sugaya, Nobuyoshi, et al.
Publicado: (2012) -
Prediction of Interactions between Viral and Host Proteins Using Supervised Machine Learning Methods
por: Barman, Ranjan Kumar, et al.
Publicado: (2014) -
Structure-based assessment and druggability classification of protein–protein interaction sites
por: Alzyoud, Lara, et al.
Publicado: (2022) -
Empirical comparison and analysis of machine learning-based approaches for druggable protein identification
por: Shoombuatong, Watshara, et al.
Publicado: (2023)