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Evolutionary Programming Applied to the Development of Quantitative Structure-Activity Relationships and Quantitative Structure-Property Relationships
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inferred← citeshttps://doi.org/10.1016/b978-0-12-409547-2.14703-1openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/b978-012213810-2/50006-2openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/b978-044452701-1.00007-7openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.chemolab.2013.07.008openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.chemolab.2015.06.016openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jmgm.2003.10.001openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/s0166-1280(98)00492-8openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci0203702openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci025580topenalex-snapshot
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Development of Binary Classification of Structural Chromosome Aberrations for a Diverse Set of Organic Compounds from Molecular Structure
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Evolved neural networks for quantitative structure-activity relationships of anti-HIV compounds
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Docking scores and QSAR using evolved neural networks for the Pan-inhibition of wild-type and mutant PfDHFR by cycloguanil derivatives
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A Comparison of Particle Swarms Techniques for the Development of Quantitative Structure-Activity Relationship Models for Drug Design
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High-Throughput Ligand Screening via Preclustering and Evolved Neural Networks
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Application of Neural Networks to Large Dataset QSAR, Virtual Screening, and Library Design
inferred← citeshttps://doi.org/10.1385/mb:27:2:139openalex-snapshot
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Applications of genetic algorithms to drug design
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Using artificial neural networks to predict cell-penetrating compounds
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inferred← citeshttps://doi.org/10.31274/etd-180810-2961openalex-snapshot
Intra and inter-brand calibration transfer for near infrared spectrometers
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Structure –Activity Relationships by Autocorrelation Descriptors and Genetic Algorithms
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