Bajorath, Jürgen

Polypharmacology: Challenges and Opportunities in Drug Discovery: Miniperspective

Anighoro, A., Bajorath, J., & Rastelli, G. (2014) · Journal of Medicinal Chemistry

Computational Drug Discovery MethodsProtein Degradation and Inhibitors

Cited by 1,131

QSAR without borders

Muratov, E. N., Bajorath, J., Sheridan, R. P., Tetko, I. V., Filimonov, D., Poroikov, V., Oprea, T. I., Baskin, I. I., Varnek, A., Roitberg, A., et al. (2020) · Chemical Society Reviews

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 913

Interpretation of machine learning models using shapley values: application to compound potency and multi-target activity predictions

Rodríguez-Pérez, R., & Bajorath, J. (2020) · Journal of Computer-Aided Molecular Design

Computational Drug Discovery MethodsExplainable Artificial Intelligence (XAI)

Cited by 718

Application of Generative Autoencoder in De Novo Molecular Design

Blaschke, T., Olivecrona, M., Engkvist, O., Bajorath, J., & Chen, H. (2018) · Molecular Informatics

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 411

SAR Index: Quantifying the Nature of Structure−Activity Relationships

Peltason, L., & Bajorath, J. (2007) · Journal of Medicinal Chemistry

Computational Drug Discovery MethodsSynthesis and Characterization of Heterocyclic Compounds

Cited by 201

Rationalizing Three-Dimensional Activity Landscapes and the Influence of Molecular Representations on Landscape Topology and the Formation of Activity Cliffs

Peltason, L., Iyer, P., & Bajorath, J. (2010) · Journal of Chemical Information and Modeling

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 85

Support-Vector-Machine-Based Ranking Significantly Improves the Effectiveness of Similarity Searching Using 2D Fingerprints and Multiple Reference Compounds

Geppert, H., Horváth, T., Gärtner, T., Wrobel, S., & Bajorath, J. (2008) · Journal of Chemical Information and Modeling

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 63

Chemoinformatics and artificial intelligence colloquium: progress and challenges in developing bioactive compounds

Bajorath, J., Chávez-Hernández, A. L., Duran-Frigola, M., Fernández-de Gortari, E., Gasteiger, J., López-López, E., Maggiora, G. M., Medina-Franco, J. L., Méndez-Lucio, O., Mestres, J., et al. (2022) · Journal of Cheminformatics

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 38

Chemoinformatics and Artificial Intelligence Colloquium: Progress and Challenges to Develop Bioactive Compounds

Bajorath, J., Chávez-Hernández, A. L., Duran-Frigola, M., Fernández-de Gortari, E., Gasteiger, J., López-López, E., Maggiora, G. M., Medina-Franco, J. L., Méndez-Lucio, O., Mestres, J., et al. (2022) · Journal of Cheminformatics

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 37