A comparison of methods for modeling quantitative structure-activity relationships.
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jCompoundMapper: An open source Java library and command-line tool for chemical fingerprintsInterpretable correlation descriptors for quantitativestructure-activity relationshipsExamining the predictive accuracy of the novel 3D N-linear algebraic molecular codifications on benchmark datasetsA constructive approach for discovering new drug leads: Using a kernel methodology for the inverse-QSAR problemBenchmarking sets for molecular dockingClassification of drug molecules considering their IC50 values using mixed-integer linear programming based hyper-boxes method.In silico prediction of estrogen receptor subtype binding affinity and selectivity using statistical methods and molecular docking with 2-arylnaphthalenes and 2-arylquinolines.Dunn's index for cluster tendency assessment of pharmacological data sets.No longer confidential: estimating the confidence of individual regression predictions.Reliably assessing prediction reliability for high dimensional QSAR data.QuBiLS-MIDAS: a parallel free-software for molecular descriptors computation based on multilinear algebraic maps.The expanding role of predictive toxicology: an update on the (Q)SAR models for mutagens and carcinogens.A model-based ensembling approach for developing QSARs.Classifying and scoring of molecules with the NGN: new datasets, significance tests, and generalization.Per aspera ad astra: application of Simplex QSAR approach in antiviral research.Robustness in experimental design: A study on the reliability of selection approachesDrug response prediction by inferring pathway-response associations with kernelized Bayesian matrix factorization.Extrapolative prediction using physically-based QSAR.High-dimensional QSAR modelling using penalized linear regression model with L1/2-norm.ChemTreeMap: an interactive map of biochemical similarity in molecular datasets.GTM-Based QSAR Models and Their Applicability Domains.A Combinational Strategy of Model Disturbance and Outlier Comparison to Define Applicability Domain in Quantitative Structural Activity Relationship.Using Local Models to Improve (Q)SAR Predictivity.The model adaptive space shrinkage (MASS) approach: a new method for simultaneous variable selection and outlier detection based on model population analysis.Estimation of the applicability domain of kernel-based machine learning models for virtual screeningDevelopment and validation of hydrophobic molecular fields derived from the quantum mechanical IEF/PCM-MST solvation models in 3D-QSAR.Ligand biological activity predictions using fingerprint-based artificial neural networks (FANN-QSAR).Rank order entropy: why one metric is not enough2D depiction of fragment hierarchies.Molecular fingerprint-based artificial neural networks QSAR for ligand biological activity predictions.The environmental fate of organic pollutants through the global microbial metabolism.CPANNatNIC software for counter-propagation neural network to assist in read-across.QNA-based 'Star Track' QSAR approach.The continuous molecular fields approach to building 3D-QSAR models.Boltzmann-Enhanced Flexible Atom-Pair Kernel with Dynamic Dimension Reduction.Quantitative structure-property relationship modeling of Grätzel solar cell dyes.Multi-Server Approach for High-Throughput Molecular Descriptors Calculation based on Multi-Linear Algebraic Maps.Exploring the QSAR's predictive truthfulness of the novel N-tuple discrete derivative indices on benchmark datasets.Integrative Modeling Strategies for Predicting Drug Toxicities at the eTOX Project.Open3DALIGN: an open-source software aimed at unsupervised ligand alignment.
P2860
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P2860
A comparison of methods for modeling quantitative structure-activity relationships.
description
2004 nî lūn-bûn
@nan
2004年の論文
@ja
2004年学术文章
@wuu
2004年学术文章
@zh
2004年学术文章
@zh-cn
2004年学术文章
@zh-hans
2004年学术文章
@zh-my
2004年学术文章
@zh-sg
2004年學術文章
@yue
2004年學術文章
@zh-hant
name
A comparison of methods for modeling quantitative structure-activity relationships.
@en
A comparison of methods for modeling quantitative structure-activity relationships.
@nl
type
label
A comparison of methods for modeling quantitative structure-activity relationships.
@en
A comparison of methods for modeling quantitative structure-activity relationships.
@nl
prefLabel
A comparison of methods for modeling quantitative structure-activity relationships.
@en
A comparison of methods for modeling quantitative structure-activity relationships.
@nl
P2093
P356
P1476
A comparison of methods for modeling quantitative structure-activity relationships.
@en
P2093
Donald F Weaver
Jeffrey J Sutherland
Lee A O'Brien
P304
P356
10.1021/JM0497141
P407
P577
2004-10-01T00:00:00Z