(Q33301559)

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Prediction and classification of drug toxicity using probabilistic modeling of temporal metabolic data: the consortium on metabonomic toxicology screening approach

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scholarly article

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Europe PubMed Central

PubMed publication ID

25 July 2017

Prediction and classification of drug toxicity using probabilistic modeling of temporal metabolic data: the consortium on metabonomic toxicology screening approach (English)

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Europe PubMed Central

PubMed publication ID

25 July 2017

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probabilistic modeling

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1

object named as

Timothy M D Ebbels

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Europe PubMed Central

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25 July 2017

Jeremy K. Nicholson

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Jeremy K Nicholson

7

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Elaine Holmes

6

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object named as

John C Lindon

5

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2

object named as

Hector C Keun

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25 July 2017

Olaf P. Beckonert

3

object named as

Olaf P Beckonert

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25 July 2017

4

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Mary E Bollard

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25 July 2017

publication date

4 October 2007

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25 July 2017

Journal of Proteome Research

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Europe PubMed Central

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25 July 2017

6

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Europe PubMed Central

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25 July 2017

11

1 reference

Europe PubMed Central

PubMed publication ID

25 July 2017

4407-4422

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Europe PubMed Central

PubMed publication ID

25 July 2017

The Consortium for Metabonomic Toxicology (COMET): aims, activities and achievements

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Analytical reproducibility in (1)H NMR-based metabonomic urinalysis

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Metabonomic characterization of genetic variations in toxicological and metabolic responses using probabilistic neural networks

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Toxicity classification from metabonomic data using a density superposition approach: ‘CLOUDS’

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Nuclear Magnetic Resonance Spectroscopic and Principal Components Analysis Investigations into Biochemical Effects of Three Model Hepatotoxins

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Assessment of Analytical Reproducibility of1H NMR Spectroscopy Based Metabonomics for Large-Scale Epidemiological Research: the INTERMAP Study

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Metabonomics: the use of electrospray mass spectrometry coupled to reversed-phase liquid chromatography shows potential for the screening of rat urine in drug development

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On Estimation of a Probability Density Function and Mode

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Chemometric Models for Toxicity Classification Based on NMR Spectra of Biofluids

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Classification of toxin-induced changes in 1H NMR spectra of urine using an artificial neural network

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High resolution proton magnetic resonance spectroscopy of biological fluids

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Statistical total correlation spectroscopy: an exploratory approach for latent biomarker identification from metabolic 1H NMR data sets

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Probabilistic neural networks

1 reference

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Predictive models of hepatotoxicity using gene expression data from primary rat hepatocytes

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Improved analysis of multivariate data by variable stability scaling: application to NMR-based metabolic profiling

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Batch statistical processing of1H NMR-derived urinary spectral data

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ANOVA-simultaneous component analysis (ASCA): a new tool for analyzing designed metabolomics data

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Automatic data reduction and pattern recognition methods for analysis of 1H nuclear magnetic resonance spectra of human urine from normal and pathological states.

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Statistical evaluation of the Predictive Toxicology Challenge 2000-2001.

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Effects of feeding and body weight loss on the 1H-NMR-based urine metabolic profiles of male Wistar Han rats: implications for biomarker discovery

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Overview of an interlaboratory collaboration on evaluating the effects of model hepatotoxicants on hepatic gene expression

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Geometric trajectory analysis of metabolic responses to toxicity can define treatment specific profiles

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Drug research. Trying to catch troublemakers with a metabolic profile

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Metabonomics: evaluation of nuclear magnetic resonance (NMR) and pattern recognition technology for rapid in vivo screening of liver and kidney toxicants

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Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings

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Contemporary issues in toxicology the role of metabonomics in toxicology and its evaluation by the COMET project

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Clustering of hepatotoxins based on mechanism of toxicity using gene expression profiles

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Comparative metabonomics of differential hydrazine toxicity in the rat and mouse

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Can the pharmaceutical industry reduce attrition rates?

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NMR-based metabonomic toxicity classification: hierarchical cluster analysis and k-nearest-neighbour approaches

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'Metabonomics': understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data

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Inverse gene expression patterns for macrophage activating hepatotoxicants and peroxisome proliferators in rat liver

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Identifiers

10.1021/PR0703021

1 reference

Europe PubMed Central

PubMed publication ID

25 July 2017

PubMed publication ID

1 reference

Europe PubMed Central

PubMed publication ID

25 July 2017

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