Machine learning-based biomarkers identification from toxicogenomics – Bridging to regulatory relevant phenotypic endpoints-Reference-Cited by-同舟云学术

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Machine learning-based biomarkers identification from toxicogenomics – Bridging to regulatory relevant phenotypic endpoints

Published:2022-02 Issue: Volume:423 Page:127141
ISSN:0304-3894
Container-title:Journal of Hazardous Materials
language:en
Short-container-title:Journal of Hazardous Materials

Author:

Rahman Sheikh Mokhlesur,Lan Jiaqi,Kaeli David,Dy Jennifer,Alshawabkeh Akram,Gu April Z.

Funder

National Science Foundation

National Institute of Environmental Health Sciences

U.S. Environmental Protection Agency

NSF

Publisher

Elsevier BV

Subject

Health, Toxicology and Mutagenesis,Pollution,Waste Management and Disposal,Environmental Chemistry,Environmental Engineering

Reference86 articles.

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2. Prediction and classification of the modes of genotoxic actions using bacterial biosensors specific for DNA damages;Ahn;Biosens. Bioelectron.,2009

3. Mixture toxicity revisited from a toxicogenomic perspective;Altenburger;Environ. Sci. Technol.,2012

4. Future water quality monitoring: improving the balance between exposure and toxicity assessments of real-world pollutant mixtures;Altenburger;Environ. Sci. Eur.,2019

5. Diagnostic tests. 1: sensitivity and specificity;Altman;BMJ,1994

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