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Sereina Riniker, Ph.D.

Affiliations: 
Chemistry Eidgenössische Technische Hochschule Zürich, Zürich, ZH, Switzerland 
Area:
Computational Chemistry
Website:
http://www.riniker.ethz.ch/people/riniker
Google:
"Sereina Riniker"
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Publications

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Esposito C, Landrum GA, Schneider N, et al. (2021) GHOST: Adjusting the Decision Threshold to Handle Imbalanced Data in Machine Learning. Journal of Chemical Information and Modeling
van Gunsteren WF, Daura X, Fuchs PFJ, et al. (2020) On the Effect of the Various Assumptions and Approximations used in Molecular Simulations on the Properties of Bio-Molecular Systems: Overview and Perspective on Issues. Chemphyschem : a European Journal of Chemical Physics and Physical Chemistry
Stadelmann T, Subramanian G, Menon S, et al. (2020) Connecting the conformational behavior of cyclic octadepsipeptides with their ionophoric property and membrane permeability. Organic & Biomolecular Chemistry
König G, Glaser N, Schroeder B, et al. (2020) An Alternative to Conventional λ-Intermediate States in Alchemical Free Energy Calculations: λ-Enveloping Distribution Sampling. Journal of Chemical Information and Modeling
Esposito C, Wang S, Lange UEW, et al. (2020) Combining Machine Learning and Molecular Dynamics to Predict P-Glycoprotein Substrates. Journal of Chemical Information and Modeling
Gebhardt J, Kiesel M, Riniker S, et al. (2020) Combining Molecular Dynamics and Machine Learning to Predict Self-Solvation Free Energies and Limiting Activity Coefficients. Journal of Chemical Information and Modeling
Awale M, Riniker S, Kramer C. (2020) Matched Molecular Series Analysis for ADME Property Prediction. Journal of Chemical Information and Modeling
Wang S, Witek J, Landrum GA, et al. (2020) Improving Conformer Generation for Small Rings and Macrocycles Based on Distance Geometry and Experimental Torsional-Angle Preferences. Journal of Chemical Information and Modeling
Riniker S, Wang S, Bleiziffer P, et al. (2019) Machine Learning with and for Molecular Dynamics Simulations. Chimia. 73: 1024-1027
Wang S, Riniker S. (2019) Use of molecular dynamics fingerprints (MDFPs) in SAMPL6 octanol-water log P blind challenge. Journal of Computer-Aided Molecular Design
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