28 results on '"Bathe, Klaus-Jürgen"'
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2. Artificial Intelligence for Risk Assessment of Cancer Therapy-Related Cardiotoxicity and Precision Cardio-Oncology
3. Powering Toxicogenomic Studies by Applying Machine Learning to Genomic Sequencing and Variant Detection
4. Deep Learning Model for Prediction of Compound Activities Over a Panel of Major Toxicity-Related Proteins
5. Machine Learning for Predicting Gas Adsorption Capacities of Metal Organic Framework
6. Identification of Structural Alerts by Machine Learning and Their Applications in Toxicology
7. Machine Learning in Prediction of Nanotoxicology
8. Computational Modeling for the Prediction of Hepatotoxicity Caused by Drugs and Chemicals
9. Machine Learning for Predicting Organ Toxicity
10. Machine Learning-Based QSAR Models and Structural Alerts for Prediction of Mitochondrial Dysfunction
11. Modeling Tox21 Data for Toxicity Prediction and Mechanism Deconvolution
12. Controlling for Confounding in Complex Survey Machine Learning Models to Assess Drug Safety and Risk
13. Mold2 Descriptors Facilitate Development of Machine Learning and Deep Learning Models for Predicting Toxicity of Chemicals
14. Machine Learning and Deep Learning Applications to Evaluate Mutagenicity
15. The Use of Machine Learning to Support Drug Safety Prediction
16. Applicability Domain Characterization for Machine Learning QSAR Models
17. Multivariate Curve Resolution for Analysis of Heterogeneous System in Toxicogenomics
18. Isalos Predictive Analytics Platform: Cheminformatics, Nanoinformatics, and Data Mining Applications
19. Quantitative Target-specific Toxicity Prediction Modeling (QTTPM): Coupling Machine Learning with Dynamic Protein–Ligand Interaction Descriptors (DyPLIDs) to Predict Androgen Receptor-mediated Toxicity
20. Optimize and Strengthen Machine Learning Models Based on in Vitro Assays with Mechanistic Knowledge and Real-World Data
21. ED Profiler: Machine Learning Tool for Screening Potential Endocrine-Disrupting Chemicals
22. Graph Kernel Learning for Predictive Toxicity Models
23. Drug Effect Deep Learner Based on Graphical Convolutional Network
24. AOP-Based Machine Learning for Toxicity Prediction
25. Multitask Learning for Quantitative Structure–Activity Relationships: A Tutorial
26. Emerging Machine Learning Techniques in Predicting Adverse Drug Reactions
27. Assessment of the Xenobiotics Toxicity Taking into Account Their Metabolism
28. Machine Learning and Deep Learning Promote Computational Toxicology for Risk Assessment of Chemicals
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