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Application of BCUT Metrics and Genetic Algorithm in Binary QSAR Analysis
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/qsar.19880070105openalex-snapshot
Crossvalidation, Bootstrapping, and Partial Least Squares Compared with Multiple Regression in Conventional QSAR Studies
inferredcites →https://doi.org/10.1006/meth.1998.0582openalex-snapshot
Use of 3D QSAR Methodology for Data Mining the National Cancer Institute Repository of Small Molecules: Application to HIV-1 Reverse Transcriptase Inhibition
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Modern Methods of Drug Discovery
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Molecular identification number for substructure searches
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Topological organic chemistry. 1. Graph theory and topological indices of alkanes
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Metric Validation and the Receptor-Relevant Subspace Concept
inferredcites →https://doi.org/10.1021/ci990032+openalex-snapshot
Construction of a Virtual High Throughput Screen by 4D-QSAR Analysis: Application to a Combinatorial Library of Glucose Inhibitors of Glycogen Phosphorylase b
inferredcites →https://doi.org/10.1021/cr9400976openalex-snapshot
Comparative QSAR: Toward a Deeper Understanding of Chemicobiological Interactions
inferredcites →https://doi.org/10.1142/9789814447300_0044openalex-snapshot
BINARY QSAR: A NEW METHOD FOR THE DETERMINATION OF QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIPS
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Combinatorial Chemistry in the Drug Discovery Process
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ChemInform Abstract: Application of BCUT Metrics and Genetic Algorithm in Binary QSAR Analysis.
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