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Classification of Highly Unbalanced CYP450 Data of Drugs Using Cost Sensitive Machine Learning Techniques

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Outgoing claims: the papers this work cites, builds on, or argues with.

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Efficient optimization of support vector machine learning parameters for unbalanced datasets
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Multivariate modeling of cytochrome P450 3A4 inhibition
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Strategies for learning in class imbalance problems
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Use of Robust Classification Techniques for the Prediction of Human Cytochrome P450 2D6 Inhibition
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Feature Selection for Descriptor Based Classification Models. 1. Theory and GA-SEC Algorithm
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Metabolic Regio- and Stereoselectivity of Cytochrome P450 2D6 towards 3,4-Methylenedioxy-N-alkylamphetamines: in Silico Predictions and Experimental Validation
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Principal Component Analysis
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Statistical Learning Theory
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Summary of information on human CYP enzymes: human P450 metabolism data
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Atomic Shielding Constants
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Analytic Atomic Wave Functions
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Training cost-sensitive neural networks with methods addressing the class imbalance problem
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GENERATION AND VALIDATION OF RAPID COMPUTATIONAL FILTERS FOR CYP2D6 AND CYP3A4
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Discriminative models for information retrieval
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Boosting SVM classifiers by ensemble
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LIBSVM
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Development of CYP3A4 Inhibition Models: Comparisons of Machine-Learning Techniques and Molecular Descriptors
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Learning One More Thing
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Prediction of Drug Metabolism: The Case of Cytochrome P450 2D6
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In Silico Methods for Predicting Ligand Binding Determinants of Cytochromes P450
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Human Cytochrome P450 Enzymes: A Status Report Summarizing Their Reactions, Substrates, Inducers, and Inhibitors
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The class imbalance problem: A systematic study1
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What's In A Name? Malay Seals As Onomastic Sources
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Advances in kernel methods: support vector learning
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Fast Training of Support Vector Machines Using Sequential Minimal Optimization

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Classification of Highly Unbalanced CYP450 Data of Drugs Using Cost Sensitive Machine Learning Techniques.
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Unbalance Quantitative Structure Activity Relationship Problem Reduction in Drug Design
inferred← citeshttps://doi.org/10.4314/jfas.1239openalex-snapshot
In vitro and in silico antioxydant activity, toxicity prediction, and molecular docking study of 3- and 3,3'-nitrophenylferrocene and their reduced amines
inferred← citeshttps://doi.org/10.55779/nsb16211823openalex-snapshot
Synthesis, characterization, cyclic voltammetry, and molecular docking studies of the antioxidant activities of superoxide anion radicals towards meso-tetramethophenyl-porphyrin and meso-tetrabiphenyl-porphyrin
inferred← citeshttps://doi.org/10.7763/ijcte.2011.v3.331openalex-snapshot
Extension of Learning Vector Quantization to Cost-sensitive Learning
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