Publication | Closed Access
Assessing Similarity and Diversity of Combinatorial Libraries by Spatial Autocorrelation Functions and Neural Networks
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Citations
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References
1996
Year
Combinatorial ChemistryBioorganic ChemistryMachine LearningEngineeringBiomolecular Structure PredictionCombinatorial LibrariesStructural BioinformaticsSimilarity MeasureMolecular BiologyDepicted Kohonen MapCombinatorial Data AnalysisMedicinal ChemistrySpatial NetworkData ScienceData MiningPattern RecognitionMolecular DiversityKohonen Neural NetworksBiochemistryKnowledge DiscoveryComputer ScienceNeural NetworksStructural BiologySpatial Autocorrelation FunctionsNatural SciencesCombinatorial Pattern MatchingSimilarity SearchDrug Discovery
Kohonen neural networks have been used to show that the combinatorial libraries derived from 1 and 2 are very similar, whereas those obtained with 3 are distinctly different. The depicted Kohonen map indicates that the libraries from 1 and 2 are so similar that they need not both be synthesized for screening. R1R4: one of 18 possible amino acid residues.
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