Cargando…
Vienna LiverTox Workspace—A Set of Machine Learning Models for Prediction of Interactions Profiles of Small Molecules With Transporters Relevant for Regulatory Agencies
Transporters expressed in the liver play a major role in drug pharmacokinetics and are a key component of the physiological bile flow. Inhibition of these transporters may lead to drug-drug interactions or even drug-induced liver injury. Therefore, predicting the interaction profile of small molecul...
Autores principales: | Montanari, Floriane, Knasmüller, Bernhard, Kohlbacher, Stefan, Hillisch, Christoph, Baierová, Christine, Grandits, Melanie, Ecker, Gerhard F. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6966498/ https://www.ncbi.nlm.nih.gov/pubmed/31998690 http://dx.doi.org/10.3389/fchem.2019.00899 |
Ejemplares similares
Ejemplares similares
-
The LiverTox Paradox-Gaps between Promised Data and Reality Check
por: Teschke, Rolf, et al.
Publicado: (2021) -
Mining hidden knowledge for drug safety assessment: topic modeling of LiverTox as a case study
por: Yu, Ke, et al.
Publicado: (2014) -
Fenofibrate‐induced hepatotoxicity: A case with a special feature that is different from those in the LiverTox database
por: Ma, Shizhan, et al.
Publicado: (2019) -
DeepCausality: A general AI-powered causal inference framework for free text: A case study of LiverTox
por: Wang, Xingqiao, et al.
Publicado: (2022) -
F1000 Workspace
por: Brody, Erica R., et al.
Publicado: (2017)