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Predicting Potent Compounds via Model-Based Global Optimization.

, , , , and . J. Chem. Inf. Model., 53 (3): 553-559 (2013)

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Parallelitätsaspekte in Da CaPo, , , and . 1. GI/ITG Arbeitstreffen zur Architektur und Implementierung von Hochleistungs-Kommunikationssystemen, Karlsruhe, Germany, (January 1994)A Run-time Environment for Da CaPo, , , and . Proceedings of International Networking Conference INET'93, page BFC-1--BFC-9. San Francisco, California, (August 1993)Similarity Searching for Potent Compounds Using Feature Selection., and . J. Chem. Inf. Model., 53 (7): 1613-1619 (2013)Design of an activity landscape view taking compound-based feature probabilities into account., , and . J. Comput. Aided Mol. Des., 28 (9): 919-926 (2014)Systematic Assessment of Compound Series with SAR Transfer Potential., , , and . J. Chem. Inf. Model., 52 (12): 3138-3143 (2012)Activity landscape image analysis using convolutional neural networks., , and . J. Cheminformatics, 12 (1): 34 (2020)Predicting the similarity search performance of fingerprints and their combination with molecular property descriptors using probabilistic and information theoretic modeling., , and . Stat. Anal. Data Min., 2 (2): 123-134 (2009)Design of chemical space networks using a Tanimoto similarity variant based upon maximum common substructures., , , and . J. Comput. Aided Mol. Des., 29 (10): 937-950 (2015)Ligand-Based Virtual Screening with Co-regularised Support Vector Regression., , , , and . ICDM Workshops, page 261-268. IEEE Computer Society, (2016)Fatigue assessment of arc welded automotive components using local stress approaches: Application to a track control arm, , and . International Journal of Fatigue, (2011)