Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules.
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DPRESS: Localizing estimates of predictive uncertaintyA Combinational Strategy of Model Disturbance and Outlier Comparison to Define Applicability Domain in Quantitative Structural Activity Relationship.A Kernel-Based Method for Assessing Uncertainty on Individual QSAR Predictions.Estimation of the applicability domain of kernel-based machine learning models for virtual screening
P2860
Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules.
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2007 nî lūn-bûn
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2007年の論文
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2007年学术文章
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2007年学术文章
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2007年学术文章
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2007年学术文章
@zh-my
2007年学术文章
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2007年學術文章
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2007年學術文章
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name
Estimating the domain of appli ...... y of drug discovery molecules.
@en
Estimating the domain of appli ...... y of drug discovery molecules.
@nl
type
label
Estimating the domain of appli ...... y of drug discovery molecules.
@en
Estimating the domain of appli ...... y of drug discovery molecules.
@nl
prefLabel
Estimating the domain of appli ...... y of drug discovery molecules.
@en
Estimating the domain of appli ...... y of drug discovery molecules.
@nl
P2093
P1476
Estimating the domain of appli ...... y of drug discovery molecules.
@en
P2093
Anton Schwaighofer
Antonius Ter Laak
Detlev Suelzle
Nikolaus Heinrich
Sebastian Mika
Timon Sebastian Schroeter
Ursula Ganzer
P2860
P2888
P304
P356
10.1007/S10822-007-9160-9
P577
2007-12-01T00:00:00Z
P5875
P6179
1052476354