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Variable Selection and Interpretation in Structure−Affinity Correlation Modeling of Estrogen Receptor Binders
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Outgoing claims: the papers this work cites, builds on, or argues with.
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QSAR study of estrogens with the help of PM3‐based descriptors
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Structure–activity relationships for gene activation oestrogenicity: Evaluation of a diverse set of aromatic chemicals
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Classification of Potential Endocrine Disrupters on the Basis of Molecular Structure Using a Nonlinear Modeling Method
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A Comparative QSAR Study Using CoMFA, HQSAR, and FRED/SKEYS Paradigms for Estrogen Receptor Binding Affinities of Structurally Diverse Compounds
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Consensus kNN QSAR: A Versatile Method for Predicting the Estrogenic Activity of Organic Compounds In Silico. A Comparative Study with Five Estrogen Receptors and a Large, Diverse Set of Ligands
inferredcites →https://doi.org/10.1080/10629360412331319808openalex-snapshot
The Impact of variable selection on the modelling of oestrogenicity
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Multivariate Analysis of Quality. An Introduction
inferredcites →https://doi.org/10.1093/toxsci/54.1.138openalex-snapshot
The Estrogen Receptor Relative Binding Affinities of 188 Natural and Xenochemicals: Structural Diversity of Ligands
inferredcites →https://doi.org/10.1351/pac200375112479openalex-snapshot
Simple, rapid assays for conventional definite testing of endocrine disruptor hazard: Summary and recommendations
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