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Frontiers in Chemistry
|
November 7, 2022
Optimizing interactions to protein binding sites by integrating docking-scoring strategies into generative AI methods
Susanne Sauer, Hans Matter, Gerhard Hessler, et al.
Journal of Chemical Information and Modeling
|
January 28, 2020
Impact of Different Automated Binding Pose Generation Approaches on Relative Binding Free Energy Simulations
Daniel Cappel, Steven Jerome, Gerhard Hessler, et al.
Future Medicinal Chemistry
|
March 1, 2014
Predictive in silico off-target profiling in drug discovery
Friedemann Schmidt, Hans Matter, Gerhard Hessler, et al.
Journal of Chemical Information and Modeling
|
September 5, 2023
Integrating Reaction Schemes, Reagent Databases, and Virtual Libraries into Fragment-Based Design by Reinforcement Learning
Susanne Sauer, Hans Matter, Gerhard Hessler, et al.
Proteins
|
April 30, 2008
SFCscore: scoring functions for affinity prediction of protein-ligand complexes
Christoph A Sotriffer, Paul Sanschagrin, Hans Matter, et al.
Journal of Medicinal Chemistry
|
March 6, 2020
Automated De Novo Design in Medicinal Chemistry: Which Types of Chemistry Does a Generative Neural Network Learn?
Christoph Grebner, Hans Matter, Alleyn T Plowright, et al.
Journal of Chemical Information and Modeling
|
January 26, 2022
Interpretation of Structure-Activity Relationships in Real-World Drug Design Data Sets Using Explainable Artificial Intelligence
Tobias Harren, Hans Matter, Gerhard Hessler, et al.
Journal of Cheminformatics
|
April 26, 2014
Quantum-mechanics-based molecular interaction fields for 3D-QSAR
Ahmed Elkerdawy, Stefan Güssregen, Hans Matter, et al.
CPT: Pharmacometrics & Systems Pharmacology
|
April 23, 2026
Machine Learning Meets Pharmacokinetics: A Comparative Analysis of Predictive Models for Plasma Concentration-Time Profiles
Felix Jost, Clemens Giegerich, Christoph Grebner, et al.
Journal of Chemical Information and Modeling
|
October 8, 2025
Upgrading Reliability in Molecular Property Prediction by Robust Quantification of Uncertainty from Machine Learning Models
Alex Kötter, Kanishka Singh, Hans Matter, et al.
Page
of 7
Search research articles
Search
Showing results (11-20 of 66) with videos related to
Sort By:
Page
of 7
Frontiers in Chemistry
|
November 7, 2022
Optimizing interactions to protein binding sites by integrating docking-scoring strategies into generative AI methods
Susanne Sauer, Hans Matter, Gerhard Hessler, et al.
Journal of Chemical Information and Modeling
|
January 28, 2020
Impact of Different Automated Binding Pose Generation Approaches on Relative Binding Free Energy Simulations
Daniel Cappel, Steven Jerome, Gerhard Hessler, et al.
Future Medicinal Chemistry
|
March 1, 2014
Predictive in silico off-target profiling in drug discovery
Friedemann Schmidt, Hans Matter, Gerhard Hessler, et al.
Journal of Chemical Information and Modeling
|
September 5, 2023
Integrating Reaction Schemes, Reagent Databases, and Virtual Libraries into Fragment-Based Design by Reinforcement Learning
Susanne Sauer, Hans Matter, Gerhard Hessler, et al.
Proteins
|
April 30, 2008
SFCscore: scoring functions for affinity prediction of protein-ligand complexes
Christoph A Sotriffer, Paul Sanschagrin, Hans Matter, et al.
Journal of Medicinal Chemistry
|
March 6, 2020
Automated De Novo Design in Medicinal Chemistry: Which Types of Chemistry Does a Generative Neural Network Learn?
Christoph Grebner, Hans Matter, Alleyn T Plowright, et al.
Journal of Chemical Information and Modeling
|
January 26, 2022
Interpretation of Structure-Activity Relationships in Real-World Drug Design Data Sets Using Explainable Artificial Intelligence
Tobias Harren, Hans Matter, Gerhard Hessler, et al.
Journal of Cheminformatics
|
April 26, 2014
Quantum-mechanics-based molecular interaction fields for 3D-QSAR
Ahmed Elkerdawy, Stefan Güssregen, Hans Matter, et al.
CPT: Pharmacometrics & Systems Pharmacology
|
April 23, 2026
Machine Learning Meets Pharmacokinetics: A Comparative Analysis of Predictive Models for Plasma Concentration-Time Profiles
Felix Jost, Clemens Giegerich, Christoph Grebner, et al.
Journal of Chemical Information and Modeling
|
October 8, 2025
Upgrading Reliability in Molecular Property Prediction by Robust Quantification of Uncertainty from Machine Learning Models
Alex Kötter, Kanishka Singh, Hans Matter, et al.
Page
of 7