A deep neural network: mechanistic hybrid model to predict pharmacokinetics in rat
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10822-023-00547-9.pdf
Reference45 articles.
1. Schneckener S et al (2019) Prediction of oral bioavailability in rats: transferring insights from in vitro correlations to (deep) machine learning models using in silico model outputs and chemical structure parameters. J Chem Inf Model 59:4893–4905
2. Tian S, Li Y, Wang J, Zhang J, Hou T (2011) ADME evaluation in drug discovery. 9. Prediction of oral bioavailability in humans based on molecular properties and structural fingerprints. Mol Pharm 8:841–851. https://doi.org/10.1021/mp100444g
3. Falcón-Cano G, Molina C, Cabrera-Pérez MÁ (2020) Adme prediction with knime: development and validation of a publicly available workflow for the prediction of human oral bioavailability. J Chem Inf Model 60:2660
4. Wu Z et al (2019) A comprehensive survey on graph neural networks. IEEE Trans Neural Netw Learn Syst 32:4
5. Zhang Z, Cui P, Zhu W (2022) Deep learning on graphs: a survey. IEEE Trans Knowl Data Eng 34:249–270
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