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Target Fishing for Chemical Compounds Using Target-Ligand Activity Data and Ranking Based Methods
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Small molecule screening by imaging
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In silico target fishing: Predicting biological targets from chemical structure
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Prediction of potential toxicity and side effect protein targets of a small molecule by a ligand–protein inverse docking approach
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Finding the target after screening the phenotype
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Lead Hopping Using SVM and 3D Pharmacophore Fingerprints
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Enhancing the Effectiveness of Virtual Screening by Fusing Nearest Neighbor Lists: A Comparison of Similarity Coefficients
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Enrichment of High-Throughput Screening Data with Increasing Levels of Noise Using Support Vector Machines, Recursive Partitioning, and Laplacian-Modified Naive Bayesian Classifiers
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Prediction of Biological Targets for Compounds Using Multiple-Category Bayesian Models Trained on Chemogenomics Databases
inferredcites →https://doi.org/10.1021/ci700369eopenalex-snapshot
Indirect Similarity Based Methods for Effective Scaffold-Hopping in Chemical Compounds
inferredcites →https://doi.org/10.1021/ci700461sopenalex-snapshot
Support-Vector-Machine-Based Ranking Significantly Improves the Effectiveness of Similarity Searching Using 2D Fingerprints and Multiple Reference Compounds
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Predictive Activity Profiling of Drugs by Topological-Fragment-Spectra-Based Support Vector Machines
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Searching for Target-Selective Compounds Using Different Combinations of Multiclass Support Vector Machine Ranking Methods, Kernel Functions, and Fingerprint Descriptors
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Prediction of Biological Targets Using Probabilistic Neural Networks and Atom-Type Descriptors
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Bridging Chemical and Biological Space: “Target Fishing” Using 2D and 3D Molecular Descriptors
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The perceptron: A probabilistic model for information storage and organization in the brain.
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Target deconvolution strategies in drug discovery
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Comparison of topological descriptors for similarity-based virtual screening using multiple bioactive reference structures
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Statistical Learning Theory
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Prediction of drug–target interaction networks from the integration of chemical and genomic spaces
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DrugBank: a comprehensive resource for in silico drug discovery and exploration
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BindingDB: a web-accessible database of experimentally determined protein-ligand binding affinities
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Comparison of Descriptor Spaces for Chemical Compound Retrieval and Classification
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Unifying collaborative and content-based filtering
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Multi-class protein fold recognition using adaptive codes
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The Multiplicity of Serotonin Receptors: Uselessly Diverse Molecules or an Embarrassment of Riches?
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Using Extended-Connectivity Fingerprints with Laplacian-Modified Bayesian Analysis in High-Throughput Screening Follow-Up
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Advances in kernel methods: support vector learning
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