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Calculation of Substructural Analysis Weights Using a Genetic Algorithm
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Evolutionary Algorithms in Molecular Design
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Relevance weighting of search terms
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Structural Key Bit Occurrence Frequencies and Dependencies in PubChem and Their Effect on Similarity Searches
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Comparison of Fragment Weighting Schemes for Substructural Analysis
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Turbo similarity searching: Effect of fingerprint and dataset on virtual‐screening performance
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Machine learning methods in chemoinformatics
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Managing bias in ROC curves
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Cheminformatics analysis and learning in a data pipelining environment
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SLASH: a program for analysing the functional groups in molecules
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Chapter 8 Machine Learning in Computational Chemistry
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Computer-Aided Selection of Novel Antitumor Drugs for Animal Screening
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Computer-aided selection of compounds for antitumor screening: validation of a statistical-heuristic method
inferredcites →https://doi.org/10.1021/ci00031a004openalex-snapshot
Selection of molecular fragment features for structure-activity studies in antitumor screening
inferredcites →https://doi.org/10.1021/ci000383kopenalex-snapshot
Robustness of Biological Activity Spectra Predicting by Computer Program PASS for Noncongeneric Sets of Chemical Compounds
inferredcites →https://doi.org/10.1021/ci034207yopenalex-snapshot
Molecular Similarity Searching Using Atom Environments, Information-Based Feature Selection, and a Naïve Bayesian Classifier
inferredcites →https://doi.org/10.1021/ci050348jopenalex-snapshot
New Methods for Ligand-Based Virtual Screening: Use of Data Fusion and Machine Learning to Enhance the Effectiveness of Similarity Searching
inferredcites →https://doi.org/10.1021/ci050353nopenalex-snapshot
Generation of a Focused Set of GSK Compounds Biased toward Ligand-Gated Ion-Channel Ligands
inferredcites →https://doi.org/10.1021/ci050374hopenalex-snapshot
Enrichment of High-Throughput Screening Data with Increasing Levels of Noise Using Support Vector Machines, Recursive Partitioning, and Laplacian-Modified Naive Bayesian Classifiers
inferredcites →https://doi.org/10.1021/ci600426eopenalex-snapshot
Evaluating Virtual Screening Methods: Good and Bad Metrics for the “Early Recognition” Problem
inferredcites →https://doi.org/10.1021/ci980332bopenalex-snapshot
Selecting Combinatorial Libraries to Optimize Diversity and Physical Properties
inferredcites →https://doi.org/10.1021/jm0010670openalex-snapshot
Discriminating between Drugs and Nondrugs by Prediction of Activity Spectra for Substances (PASS)
inferredcites →https://doi.org/10.1021/jm00214a002openalex-snapshot
A statistical-heuristic method for automated selection of drugs for screening
inferredcites →https://doi.org/10.1021/jm00251a014openalex-snapshot
Substructural analysis. Novel approach to the problem of drug design
inferredcites →https://doi.org/10.1021/jm0303195openalex-snapshot
Classification of Kinase Inhibitors Using a Bayesian Model
inferredcites →https://doi.org/10.1021/jm049970dopenalex-snapshot
Combination of a Naive Bayes Classifier with Consensus Scoring Improves Enrichment of High-Throughput Docking Results
inferredcites →https://doi.org/10.1021/jm9602928openalex-snapshot
The Properties of Known Drugs. 1. Molecular Frameworks
inferredcites →https://doi.org/10.1039/p19720002428openalex-snapshot
Analysis of structural characteristics of chemical compounds in a large computer-based file. Part III. Statistical association of fragment incidence
inferredcites →https://doi.org/10.1093/bioinformatics/16.8.747openalex-snapshot
PASS: prediction of activity spectra for biologically active substances
inferredcites →https://doi.org/10.1093/comjnl/26.3.239openalex-snapshot
The Retrieval Effects of Query Expansion on a Feedback Document Retrieval System
inferredcites →https://doi.org/10.1108/eb026637openalex-snapshot
A THEORETICAL BASIS FOR THE USE OF CO‐OCCURRENCE DATA IN INFORMATION RETRIEVAL
inferredcites →https://doi.org/10.1177/1087057105281365openalex-snapshot
Using Extended-Connectivity Fingerprints with Laplacian-Modified Bayesian Analysis in High-Throughput Screening Follow-Up
inferredcites →https://doi.org/10.2174/138620709788167962openalex-snapshot
Performance of Machine Learning Methods for Ligand-Based Virtual Screening
inferredcites →https://doi.org/10.2174/138620709788167980openalex-snapshot
Machine Learning in Virtual Screening
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