Publications by authors named "Christian Feldmann"

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Analysis of uncertainty of neural fingerprint-based models.
Christian W Feldmann, Jochen Sieg, Miriam Mathea

Faraday Discuss· January 2025

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MolPipeline: A Python Package for Processing Molecules with RDKit in Scikit-learn.
Jochen Sieg, Christian W Feldmann, Jennifer Hemmerich, Conrad Stork, Frederik Sandfort

J Chem Inf Model· December 2024

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Calculation of exact Shapley values for explaining support vector machine models using the radial basis function kernel.
Andrea Mastropietro, Christian Feldmann, Jürgen Bajorath

Sci Rep· November 2023

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Advances in Computational Polypharmacology.
Christian Feldmann, Jürgen Bajorath

Mol Inform· December 2022

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EdgeSHAPer: Bond-centric Shapley value-based explanation method for graph neural networks.
Andrea Mastropietro, Giuseppe Pasculli, Christian Feldmann, Raquel Rodríguez-Pérez, Jürgen Bajorath

iScience· October 2022

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Calculation of exact Shapley values for support vector machines with Tanimoto kernel enables model interpretation.
Christian Feldmann, Jürgen Bajorath

iScience· September 2022

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Differentiating Inhibitors of Closely Related Protein Kinases with Single- or Multi-Target Activity via Explainable Machine Learning and Feature Analysis.
Christian Feldmann, Jürgen Bajorath

Biomolecules· April 2022

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Explainable machine learning predictions of dual-target compounds reveal characteristic structural features.
Christian Feldmann, Maren Philipps, Jürgen Bajorath

Sci Rep· November 2021

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Machine learning reveals that structural features distinguishing promiscuous and non-promiscuous compounds depend on target combinations.
Christian Feldmann, Jürgen Bajorath

Sci Rep· April 2021

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Structured data sets of compounds with multi-target and corresponding single-target activity from biological assays.
Christian Feldmann, Dimitar Yonchev, Jürgen Bajorath

Future Sci OA· March 2021

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Prediction of Promiscuity Cliffs Using Machine Learning.
Thomas Blaschke, Christian Feldmann, Jürgen Bajorath

Mol Inform· January 2021

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Systematic Data Analysis and Diagnostic Machine Learning Reveal Differences between Compounds with Single- and Multitarget Activity.
Christian Feldmann, Dimitar Yonchev, Dagmar Stumpfe, Jürgen Bajorath

Mol Pharm· December 2020

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Analysis of Biological Screening Compounds with Single- or Multi-Target Activity via Diagnostic Machine Learning.
Christian Feldmann, Dimitar Yonchev, Jürgen Bajorath

Biomolecules· November 2020

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N-Sulfonyl dipeptide nitriles as inhibitors of human cathepsin S: In silico design, synthesis and biochemical characterization.
Carina Lemke, Lorenzo Cianni, Christian Feldmann, Erik Gilberg, Jiafei Yin

Bioorg Med Chem Lett· September 2020

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X-ray Structure-Based Chemoinformatic Analysis Identifies Promiscuous Ligands Binding to Proteins from Different Classes with Varying Shapes.
Christian Feldmann, Jürgen Bajorath

Int J Mol Sci· May 2020

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Mapping the S1 and S1' subsites of cysteine proteases with new dipeptidyl nitrile inhibitors as trypanocidal agents.
Lorenzo Cianni, Carina Lemke, Erik Gilberg, Christian Feldmann, Fabiana Rosini

PLoS Negl Trop Dis· March 2020

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Biological Activity Profiles of Multitarget Ligands from X-ray Structures.
Christian Feldmann, Jürgen Bajorath

Molecules· February 2020

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Can Cysteine Protease Cross-Class Inhibitors Achieve Selectivity?
Lorenzo Cianni, Christian Wolfgang Feldmann, Erik Gilberg, Michael Gütschow, Luiz Juliano

J Med Chem· December 2019

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Identifying Promiscuous Compounds with Activity against Different Target Classes.
Christian Feldmann, Filip Miljković, Dimitar Yonchev, Jürgen Bajorath

Molecules· November 2019

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