Andreas H. Göller
Orcid: 0000-0003-4343-4063
According to our database1,
Andreas H. Göller
authored at least 18 papers
between 2006 and 2024.
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Bibliography
2024
Comparative assessment of physics-based in silico methods to calculate relative solubilities.
J. Comput. Aided Mol. Des., December, 2024
J. Comput. Aided Mol. Des., December, 2024
MELLODDY: Cross-pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR without Compromising Proprietary Information.
J. Chem. Inf. Model., 2024
2023
Predicting absolute aqueous solubility by applying a machine learning model for an artificially liquid-state as proxy for the solid-state.
J. Comput. Aided Mol. Des., December, 2023
pH-dependent solubility prediction for optimized drug absorption and compound uptake by plants.
J. Comput. Aided Mol. Des., March, 2023
2022
Reliable gas-phase tautomer equilibria of drug-like molecule scaffolds and the issue of continuum solvation.
J. Comput. Aided Mol. Des., 2022
2021
J. Cheminformatics, 2021
RegioSQM20: improved prediction of the regioselectivity of electrophilic aromatic substitutions.
J. Cheminformatics, 2021
Combined experimental and quantum mechanical elucidation of the synthetically accessible stereoisomers of Hydroxyestradienone (HED), the starting material for vilaprisan synthesis.
J. Comput. Aided Mol. Des., 2021
J. Comput. Aided Mol. Des., 2021
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., 2019
Mechanistic Reactivity Descriptors for the Prediction of Ames Mutagenicity of Primary Aromatic Amines.
J. Chem. Inf. Model., 2019
Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies.
J. Cheminformatics, 2019
2018
Reliable and Performant Identification of Low-Energy Conformers in the Gas Phase and Water.
J. Chem. Inf. Model., 2018
2015
Best of Both Worlds: Combining Pharma Data and State of the Art Modeling Technology To Improve <i>in Silico</i> p<i>K</i><sub>a</sub> Prediction.
J. Chem. Inf. Model., 2015
2013
2009
Similarity-Based Classifier Using Topomers to Provide a Knowledge Base for hERG Channel Inhibition.
J. Chem. Inf. Model., 2009
2006
In Silico Prediction of Buffer Solubility Based on Quantum-Mechanical and HQSAR- and Topology-Based Descriptors.
J. Chem. Inf. Model., 2006