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Jackknife-Based Selection of Gram−Schmidt Orthogonalized Descriptors in QSAR

https://doi.org/10.1021/ci100169p
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/cem.1073openalex-snapshot
Correlation weighted successive projections algorithm as a novel method for variable selection in QSAR studies: investigation of anti‐HIV activity of HEPT derivatives
inferredcites →https://doi.org/10.1002/cem.1192openalex-snapshot
Sorting variables by using informative vectors as a strategy for feature selection in multivariate regression
inferredcites →https://doi.org/10.1002/cem.915openalex-snapshot
The prediction error in CLS and PLS: the importance of feature selection prior to multivariate calibration
inferredcites →https://doi.org/10.1002/cem.971openalex-snapshot
Application of radial basis function networks and successive projections algorithm in a QSAR study of anti‐HIV activity for a large group of HEPT derivatives
inferredcites →https://doi.org/10.1002/qsar.19940130104openalex-snapshot
On Identifying Likely Determinants of Biological Activity in High Dimensional QSAR Problems
inferredcites →https://doi.org/10.1002/qsar.19940130306openalex-snapshot
Variable Selection in QSAR Studies. I. An Evolutionary Algorithm
inferredcites →https://doi.org/10.1016/j.aca.2003.12.010openalex-snapshot
Detecting “bad” regression models: multicriteria fitness functions in regression analysis
inferredcites →https://doi.org/10.1016/j.aca.2007.04.009openalex-snapshot
Quantitative structure–retention relationship for the Kovats retention indices of a large set of terpenes: A combined data splitting-feature selection strategy
inferredcites →https://doi.org/10.1016/j.aca.2009.05.005openalex-snapshot
An efficient variable selection method based on the use of external memory in ant colony optimization. Application to QSAR/QSPR studies
inferredcites →https://doi.org/10.1016/j.chemolab.2004.06.004openalex-snapshot
A two-stage evolutionary algorithm for variable selection in the development of RBF neural network models
inferredcites →https://doi.org/10.1016/j.chemolab.2004.12.011openalex-snapshot
Performance of some variable selection methods when multicollinearity is present
inferredcites →https://doi.org/10.1016/j.chemolab.2006.03.001openalex-snapshot
Quantitative Structure–Activity Relationship (QSAR) modeling of juvenile hormone activity: Comparison of validation procedures
inferredcites →https://doi.org/10.1016/j.chemolab.2006.04.021openalex-snapshot
Reducing over-optimism in variable selection by cross-model validation
inferredcites →https://doi.org/10.1016/j.chemolab.2007.11.005openalex-snapshot
Successive projections algorithm combined with uninformative variable elimination for spectral variable selection
inferredcites →https://doi.org/10.1016/j.chemolab.2009.04.006openalex-snapshot
A wavelength selection method based on randomization test for near-infrared spectral analysis
inferredcites →https://doi.org/10.1016/j.tox.2005.11.024openalex-snapshot
Quantitative structure activity relationship for the computational prediction of nitrocompounds carcinogenicity
inferredcites →https://doi.org/10.1016/s0165-9936(03)00607-1openalex-snapshot
Cross-validation as the objective function for variable-selection techniques
inferredcites →https://doi.org/10.1016/s0169-7439(00)00102-7openalex-snapshot
The bootstrap: a tutorial
inferredcites →https://doi.org/10.1016/s0169-7439(01)00119-8openalex-snapshot
The successive projections algorithm for variable selection in spectroscopic multicomponent analysis
inferredcites →https://doi.org/10.1016/s0950-3293(99)00039-7openalex-snapshot
Modified Jack-knife estimation of parameter uncertainty in bilinear modelling by partial least squares regression (PLSR)
inferredcites →https://doi.org/10.1021/ci00002a018openalex-snapshot
Resolution of ambiguities in structure-property studies by use of orthogonal descriptors
inferredcites →https://doi.org/10.1021/ci0001177openalex-snapshot
QSAR with Few Compounds and Many Features
inferredcites →https://doi.org/10.1021/ci0001435openalex-snapshot
QSAR Modeling with the Electrotopological State: TIBO Derivatives
inferredcites →https://doi.org/10.1021/ci00020a020openalex-snapshot
Application of Genetic Function Approximation to Quantitative Structure-Activity Relationships and Quantitative Structure-Property Relationships
inferredcites →https://doi.org/10.1021/ci00022a009openalex-snapshot
Evolutionary Programming Applied to the Development of Quantitative Structure-Activity Relationships and Quantitative Structure-Property Relationships
inferredcites →https://doi.org/10.1021/ci00023a011openalex-snapshot
Automated Descriptor Selection for Quantitative Structure-Activity Relationships Using Generalized Simulated Annealing
inferredcites →https://doi.org/10.1021/ci000384copenalex-snapshot
Unsupervised Forward Selection: A Method for Eliminating Redundant Variables
inferredcites →https://doi.org/10.1021/ci000450aopenalex-snapshot
Use of Automatic Relevance Determination in QSAR Studies Using Bayesian Neural Networks
inferredcites →https://doi.org/10.1021/ci010247vopenalex-snapshot
Genetic Algorithm Guided Selection: Variable Selection and Subset Selection
inferredcites →https://doi.org/10.1021/ci020377jopenalex-snapshot
VSMP: A Novel Variable Selection and Modeling Method Based on the Prediction
inferredcites →https://doi.org/10.1021/ci025636jopenalex-snapshot
Toward Generating Simpler QSAR Models: Nonlinear Multivariate Regression versus Several Neural Network Ensembles and Some Related Methods
inferredcites →https://doi.org/10.1021/ci0342167openalex-snapshot
QSPR Study on the Bioconcentration Factors of Nonionic Organic Compounds in Fish by Characteristic Root Index and Semiempirical Molecular Descriptors
inferredcites →https://doi.org/10.1021/ci050215yopenalex-snapshot
Quantitative Structure−Activity Relationship Modeling of Juvenile Hormone Mimetic Compounds forCulexPipiensLarvae, with a Discussion of Descriptor-Thinning Methods
inferredcites →https://doi.org/10.1021/ci700283sopenalex-snapshot
Statistical Confidence for Variable Selection in QSAR Models via Monte Carlo Cross-Validation
inferredcites →https://doi.org/10.1021/ci900115yopenalex-snapshot
Comments on the Definition of the Q 2 Parameter for QSAR Validation
inferredcites →https://doi.org/10.1021/ci980405ropenalex-snapshot
Development and Validation of a Novel Variable Selection Technique with Application to Multidimensional Quantitative Structure−Activity Relationship Studies
inferredcites →https://doi.org/10.1021/jf0704211openalex-snapshot
Quantitative Structure−Antifungal Activity Relationships of Some Benzohydrazides against Botrytis cinerea
inferredcites →https://doi.org/10.1021/jm00163a023openalex-snapshot
Structure-activity relationships of antifilarial antimycin analogs: a multivariate pattern recognition study
inferredcites →https://doi.org/10.1021/jm00185a010openalex-snapshot
Confidence interval estimators for parameters associated with quantitative structure-activity relationships
inferredcites →https://doi.org/10.1021/jm00280a017openalex-snapshot
Chance correlations in structure-activity studies using multiple regression analysis
inferredcites →https://doi.org/10.1021/jm0104668openalex-snapshot
Feature Selection for Structure−Activity Correlation Using Binary Particle Swarms
inferredcites →https://doi.org/10.1039/b803687jopenalex-snapshot
Near-infrared reflectance spectroscopy and multivariate calibration techniques applied to modelling the crude protein, fibre and fat content in rapeseed meal
inferredcites →https://doi.org/10.1080/10629360601033671openalex-snapshot
A quantitative structure–activity relationship (QSAR) study of dermal absorption using theoretical molecular descriptors
inferredcites →https://doi.org/10.1214/aos/1193342379openalex-snapshot
A Statistical Theory of Calibration
inferredcites →https://doi.org/10.1255/jnirs.271openalex-snapshot
Variable Selection in near Infrared Spectroscopy Based on Significance Testing in Partial Least Squares Regression

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4870259openalex-extracted
Generalized Classical Least Squares: Toward Unifying Classical and Inverse Calibrations
inferred← citeshttps://doi.org/10.1002/9781118783344.ch6openalex-snapshot
Maximizing the Power of a Local Model for ADMET‐Property Prediction
inferred← citeshttps://doi.org/10.1007/s00044-012-0453-8openalex-snapshot
Linear and nonlinear QSAR modeling of 1,3,8-substituted-9-deazaxanthines as potential selective A2BAR antagonists
inferred← citeshttps://doi.org/10.1007/s13738-026-03374-5openalex-snapshot
Random augmented inverse least squares
inferred← citeshttps://doi.org/10.1016/j.chemolab.2013.07.008openalex-snapshot
Uninformative variable elimination assisted by Gram–Schmidt Orthogonalization/successive projection algorithm for descriptor selection in QSAR
inferred← citeshttps://doi.org/10.1016/j.chemolab.2013.08.004openalex-snapshot
Unsupervised selection of informative descriptors in QSAR study of anti-HIV activities of HEPT derivatives
inferred← citeshttps://doi.org/10.1016/j.chemolab.2014.04.005openalex-snapshot
Replacement based non-linear data reduction in radial basis function networks QSAR modeling
inferred← citeshttps://doi.org/10.1016/j.chemolab.2016.01.007openalex-snapshot
Type (I, II) errors variable selection in quantitative structure activity relationships
inferred← citeshttps://doi.org/10.1016/j.trac.2012.09.006openalex-snapshot
The successive projections algorithm
inferred← citeshttps://doi.org/10.1021/ci500152bopenalex-snapshot
Integrative and Personalized QSAR Analysis in Cancer by Kernelized Bayesian Matrix Factorization
inferred← citeshttps://doi.org/10.1039/c8cp07002dopenalex-snapshot
Development and application of a comprehensive machine learning program for predicting molecular biochemical and pharmacological properties
inferred← citeshttps://doi.org/10.1080/1062936x.2015.1120779openalex-snapshot
A comprehensive QSPR model for dielectric constants of binary solvent mixtures
inferred← citeshttps://doi.org/10.3390/ijms222010995openalex-snapshot
Quantum Artificial Neural Network Approach to Derive a Highly Predictive 3D-QSAR Model for Blood–Brain Barrier Passage
inferred← citeshttps://doi.org/10.4028/www.scientific.net/amm.472.764openalex-snapshot
The Anti-Influenza Activity of Cyclohexene Derivatives Studied by Topological Indices and Neural Network
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