Ensembles of Bayesian-regularized genetic neural networks for modeling of acetylcholinesterase inhibition by huprines.
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Predicting complex quantitative traits with Bayesian neural networks: a case study with Jersey cows and wheat.Computational analysis of HIV-1 protease protein binding pockets.Genetic algorithm optimization in drug design QSAR: Bayesian-regularized genetic neural networks (BRGNN) and genetic algorithm-optimized support vectors machines (GA-SVM).Qualitative and quantitative structure-activity relationship modelling for predicting blood-brain barrier permeability of structurally diverse chemicals.A study of genetic algorithm evolution on the lipophilicity of polychlorinated biphenyls.Prediction of body mass index in mice using dense molecular markers and a regularized neural network.An Accurate and Efficient Method to Predict Y-NO Bond Homolysis Bond Dissociation Energies
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P2860
Ensembles of Bayesian-regularized genetic neural networks for modeling of acetylcholinesterase inhibition by huprines.
description
2006 nî lūn-bûn
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2006年の論文
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2006年学术文章
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name
Ensembles of Bayesian-regulari ...... terase inhibition by huprines.
@en
Ensembles of Bayesian-regulari ...... terase inhibition by huprines.
@nl
type
label
Ensembles of Bayesian-regulari ...... terase inhibition by huprines.
@en
Ensembles of Bayesian-regulari ...... terase inhibition by huprines.
@nl
prefLabel
Ensembles of Bayesian-regulari ...... terase inhibition by huprines.
@en
Ensembles of Bayesian-regulari ...... terase inhibition by huprines.
@nl
P2860
P1476
Ensembles of Bayesian-regulari ...... terase inhibition by huprines.
@en
P2093
Michael Fernández
P2860
P304
P356
10.1111/J.1747-0285.2006.00435.X
P577
2006-10-01T00:00:00Z