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The Receptor-like Neural Network for Modeling Corticosteroid and Testosterone Binding Globulins
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Abbildung elektrostatischer Potentiale muscarinischer und nicotinischer Agonisten mit künstlichen neuronalen Netzen
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Synthese von natürlich vorkommendem (−)‐Calyculin A
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Self-Organization and Associative Memory
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Steric Effects in Drug Design.
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Modeling Drug–Receptor Interactions
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Steroid-protein interactions. Human corticosteroid binding globulin: some physicochemical properties and binding specificity
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Representation of Molecular Electrostatic Potentials by Topological Feature Maps
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Autocorrelation of Molecular Surface Properties for Modeling Corticosteroid Binding Globulin and Cytosolic Ah Receptor Activity by Neural Networks
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A QSAR investigation of dihydrofolate reductase inhibition by Baker triazines based upon molecular shape analysis
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Photoassisted water-gas shift reaction over platinized titanium dioxide catalysts
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Theory and application of molecular potential energy fields in molecular shape analysis: a quantitative structure-activity relationship study of 2,4-diamino-5-benzylpyrimidines as dihydrofolate reductase inhibitors
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Combined distance geometry analysis of dihydrofolate reductase inhibition by quinazolines and triazines
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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ChemInform Abstract: The Receptor‐Like Neural Network for Modeling Corticosteroid and Testosterone Binding Globulins.
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Computer Representation of Chemical Compounds
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Computer Representation of Chemical Compounds
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Three-Dimensional Quantitative Structure–Activity Relationship: The State of the Art
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QSAR modeling of globulin binding affinity of corticosteroids using AM1 calculations
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Three dimensional holographic vector of atomic interaction field (3D-HoVAIF)
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Self-organizing neural networks for pharmacophore mapping
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E-State Modeling of Corticosteroids Binding AffinityValidation of Model for Small Data Set
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QSAR modeling with the electrotopological state indices: Corticosteroids
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QuBiLS-MAS, open source multi-platform software for atom- and bond-based topological (2D) and chiral (2.5D) algebraic molecular descriptors computations
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Applications of soft computing in drug design
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Self-organizing neural network for modeling 3D QSAR of colchicinoids.
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Receptor Dependent Multidimensional QSAR for Modeling Drug - Receptor Interactions
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Functional and Material Properties in Nanocatalyst Design: A Data Handling and Sharing Problem
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Unsupervised Learning in Drug Design from Self-Organization to Deep Chemistry
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