A novel RBF neural network training methodology to predict toxicity to Vibrio fischeri.
about
Searching for anthranilic acid-based thumb pocket 2 HCV NS5B polymerase inhibitors through a combination of molecular docking, 3D-QSAR and virtual screening.Machine learning-based models to predict modes of toxic action of phenols to Tetrahymena pyriformis.Evolving RBF neural networks for adaptive soft-sensor design.Theoretical study of GSK-3α: neural networks QSAR studies for the design of new inhibitors using 2D descriptors.
P2860
A novel RBF neural network training methodology to predict toxicity to Vibrio fischeri.
description
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name
A novel RBF neural network training methodology to predict toxicity to Vibrio fischeri.
@en
A novel RBF neural network training methodology to predict toxicity to Vibrio fischeri.
@nl
type
label
A novel RBF neural network training methodology to predict toxicity to Vibrio fischeri.
@en
A novel RBF neural network training methodology to predict toxicity to Vibrio fischeri.
@nl
prefLabel
A novel RBF neural network training methodology to predict toxicity to Vibrio fischeri.
@en
A novel RBF neural network training methodology to predict toxicity to Vibrio fischeri.
@nl
P50
P1433
P1476
A novel RBF neural network training methodology to predict toxicity to Vibrio fischeri.
@en
P2093
Olga Igglessi-Markopoulou
P2888
P304
P356
10.1007/S11030-005-9008-Y
P577
2006-05-01T00:00:00Z