Binary classification models for endocrine disrupter effects mediated through the estrogen receptor.
about
CERAPP: Collaborative Estrogen Receptor Activity Prediction ProjectRigorous 3-dimensional spectral data activity relationship approach modeling strategy for ToxCast estrogen receptor data classification, validation, and feature extraction.Computational structure-activity relationship analysis of small-molecule agonists for human formyl peptide receptors.Decision tree models for data mining in hit discovery.Internet resources for agent-based modelling.Assessment of hydroxylated metabolites of polychlorinated biphenyls as potential xenoestrogens: a QSAR comparative analysis∗.QSAR classification of estrogen receptor binders and pre-screening of potential pleiotropic EDCs.QSAR classification models for the screening of the endocrine-disrupting activity of perfluorinated compounds.Prediction of the endocrine disruption profile of pesticides.m-Phenylenediamine and m-Phenylenediamine Sulfate.QSAR prediction of the competitive interaction of emerging halogenated pollutants with human transthyretin.
P2860
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P2860
Binary classification models for endocrine disrupter effects mediated through the estrogen receptor.
description
2008 nî lūn-bûn
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2008年の論文
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2008年学术文章
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2008年学术文章
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2008年学术文章
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2008年学术文章
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2008年学术文章
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2008年學術文章
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name
Binary classification models f ...... through the estrogen receptor.
@en
Binary classification models f ...... through the estrogen receptor.
@nl
type
label
Binary classification models f ...... through the estrogen receptor.
@en
Binary classification models f ...... through the estrogen receptor.
@nl
prefLabel
Binary classification models f ...... through the estrogen receptor.
@en
Binary classification models f ...... through the estrogen receptor.
@nl
P2093
P2860
P1476
Binary classification models f ...... through the estrogen receptor.
@en
P2093
A Roncaglioni
P2860
P304
P356
10.1080/10629360802550606
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2008-01-01T00:00:00Z