(Q35758123)

10 August 2017

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title

Performance of (consensus) kNN QSAR for predicting estrogenic activity in a large diverse set of organic compounds (English)

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10 August 2017

Asikainen AH

1

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10 August 2017

Ruuskanen J

series ordinal

2

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10 August 2017

Tuppurainen KA

series ordinal

3

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10 August 2017

publication date

1 February 2004

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SAR and QSAR in Environmental Research

10 August 2017

published in

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10 August 2017

volume

15

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10 August 2017

issue

1

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10 August 2017

page(s)

19-32

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The estradiol pharmacophore: ligand structure-estrogen receptor binding affinity relationships and a model for the receptor binding site

10 August 2017

cites work

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Structure-activity relationships for a large diverse set of natural, synthetic, and environmental estrogens

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Ligand-based identification of environmental estrogens.

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Induction of the estrogen specific mitogenic response of MCF-7 cells by selected analogues of estradiol-17 beta: a 3D QSAR study

21 January 2018

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Quantitative structure-activity relationships (QSARs) for estrogen binding to the estrogen receptor: predictions across species

21 January 2018

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Evaluation of quantitative structure-activity relationship methods for large-scale prediction of chemicals binding to the estrogen receptor.

21 January 2018

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Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins

21 January 2018

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Use of 13C NMR spectrometric data to produce a predictive model of estrogen receptor binding activity

21 January 2018

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Novel variable selection quantitative structure--property relationship approach based on the k-nearest-neighbor principle

21 January 2018

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Selecting screening candidates for kinase and G protein-coupled receptor targets using neural networks.

21 January 2018

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Simulating lipophilicity of organic molecules with a back-propagation neural network.

21 January 2018

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Neural network studies. 4. Introduction to associative neural networks.

21 January 2018

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Development of quantitative structure-activity relationships and classification models for anticonvulsant activity of hydantoin analogues

21 January 2018

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Predicting the genotoxicity of secondary and aromatic amines using data subsetting to generate a model ensemble

21 January 2018

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GRID/CPCA: a new computational tool to design selective ligands.

21 January 2018

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Decision forest: combining the predictions of multiple independent decision tree models

21 January 2018

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Decision tree SAR models for developmental toxicity based on an FDA/TERIS database

21 January 2018

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Development and use of quantum mechanical molecular models. 76. AM1: a new general purpose quantum mechanical molecular model

21 January 2018

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Equation of State Calculations by Fast Computing Machines

21 January 2018

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Optimization by Simulated Annealing

21 January 2018

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21 January 2018

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Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection

21 January 2018

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Evaluation of a novel electronic eigenvalue (EEVA) molecular descriptor for QSAR/QSPR studies: validation using a benchmark steroid data set.

21 January 2018

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Prediction of n-octanol/water partition coefficients from PHYSPROP database using artificial neural networks and E-state indices.

21 January 2018

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Estimation of aqueous solubility of chemical compounds using E-state indices

21 January 2018

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QSAR modeling using chirality descriptors derived from molecular topology

21 January 2018

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https://api.crossref.org/works/10.1080%2F1062936032000169642

The Importance of Being Earnest: Validation is the Absolute Essential for Successful Application and Interpretation of QSPR Models

21 January 2018

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Application of Associative Neural Networks for Prediction of Lipophilicity in ALOGPS 2.1 Program

21 January 2018

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A testing deadline for endocrine disrupters

21 January 2018

1 reference

https://api.crossref.org/works/10.1080%2F1062936032000169642

10.1080/1062936032000169642

21 January 2018

Identifiers

DOI

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10 August 2017

1 reference