Chemical language models for molecular design von Bajorath, Jürgen

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Interpretation of Compound Activity Predictions from Complex Machine Learning Models Using Local Approximations and Shapley Values von Rodríguez-Pérez, Raquel, Bajorath, Jürgen

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Recent Advances in Scaffold Hopping von Hu, Ye, Stumpfe, Dagmar, Bajorath, Jürgen

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Interpretation of machine learning models using shapley values: application to compound potency and multi-target activity predictions von Rodríguez-Pérez, Raquel, Bajorath, Jürgen

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Molecular similarity in medicinal chemistry von Maggiora, Gerald, Vogt, Martin, Stumpfe, Dagmar, Bajorath, Jürgen

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Polypharmacology: challenges and opportunities in drug discovery von Anighoro, Andrew, Bajorath, Jürgen, Rastelli, Giulio

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Generative kinase inhibitor modeling viewed from a medicinal chemistry perspective von Bajorath, Jürgen

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Evolution of Support Vector Machine and Regression Modeling in Chemoinformatics and Drug Discovery von Rodríguez-Pérez, Raquel, Bajorath, Jürgen

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Molecular Similarity Concepts for Informatics Applications von Bajorath, Jürgen

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Exploring Activity Cliffs in Medicinal Chemistry: Miniperspective von Stumpfe, Dagmar, Bajorath, Jürgen

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Explainable machine learning for medicinal chemistry: exploring multi-target compounds von Bajorath, Jürgen

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Data-oriented protein kinase drug discovery von Xerxa, Elena, Bajorath, Jürgen

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How Frequently Are Pan-Assay Interference Compounds Active? Large-Scale Analysis of Screening Data Reveals Diverse Activity Profiles, Low Global Hit Frequency, and Many Consistentl... von Jasial, Swarit, Hu, Ye, Bajorath, Jürgen

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Computational Exploration of Molecular Scaffolds in Medicinal Chemistry von Hu, Ye, Stumpfe, Dagmar, Bajorath, Jürgen

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Minimal screening requirements for identifying highly promiscuous kinase inhibitors von Bajorath, Jürgen

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Recent progress in understanding activity cliffs and their utility in medicinal chemistry von Stumpfe, Dagmar, Hu, Ye, Dimova, Dilyana, Bajorath, Jürgen

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Fine-tuning of a generative neural network for designing multi-target compounds von Blaschke, Thomas, Bajorath, Jürgen

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Rationalizing Predictions of Isoform-Selective Phosphoinositide 3‑Kinase Inhibitors Using MolAnchor Analysis von Lamens, Alec, Bajorath, Jürgen

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Influence of Data Curation and Confidence Levels on Compound Predictions Using Machine Learning Models von Xerxa, Elena, Vogt, Martin, Bajorath, Jürgen

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Chemical and biological language models in molecular design: opportunities, risks and scientific reasoning von Bajorath, Jürgen

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