Cargando…
Data structures for compound promiscuity analysis: promiscuity cliffs, pathways and promiscuity hubs formed by inhibitors of the human kinome
AIM: A large collection of promiscuity cliffs (PCs), PC pathways (PCPs) and promiscuity hubs (PHs) formed by inhibitors of human kinases is made freely available. METHODOLOGY: Inhibitor PCs were systematically identified and organized in network representations, from which PCPs were extracted. PH co...
Autores principales: | Miljković, Filip, Bajorath, Jürgen |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Future Science Ltd
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6695529/ https://www.ncbi.nlm.nih.gov/pubmed/31428450 http://dx.doi.org/10.2144/fsoa-2019-0040 |
Ejemplares similares
-
Prediction of Promiscuity Cliffs Using Machine Learning
por: Blaschke, Thomas, et al.
Publicado: (2020) -
Identifying Promiscuous Compounds with Activity against Different Target Classes
por: Feldmann, Christian, et al.
Publicado: (2019) -
Machine learning reveals that structural features distinguishing promiscuous and non-promiscuous compounds depend on target combinations
por: Feldmann, Christian, et al.
Publicado: (2021) -
High-resolution view of compound promiscuity
por: Hu, Ye, et al.
Publicado: (2013) -
Promiscuity progression of bioactive compounds over time
por: Hu, Ye, et al.
Publicado: (2015)