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Guided optimization of ToxPi model weights using a Semi-Automated approach.

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第一作者： Jonathon F,Fleming

第一单位： North Carolina State University, Bioinformatics Research Center, Raleigh, NC 27695, USA.;National Institute of Environmental Health Sciences, Biostatistics and Computational Biology Branch, Durham, NC 27713, USA.

作者： Jonathon F,Fleming ^[1] ; John S,House ^[2] ; Jessie R,Chappel ^[3] ; Alison A,Motsinger-Reif ^[2] ; David M,Reif ^[4]

作者单位： North Carolina State University, Bioinformatics Research Center, Raleigh, NC 27695, USA.;National Institute of Environmental Health Sciences, Biostatistics and Computational Biology Branch, Durham, NC 27713, USA. ^[1] National Institute of Environmental Health Sciences, Biostatistics and Computational Biology Branch, Durham, NC 27713, USA. ^[2] North Carolina State University, Bioinformatics Research Center, Raleigh, NC 27695, USA. ^[3] North Carolina State University, Bioinformatics Research Center, Raleigh, NC 27695, USA.;National Institute of Environmental Health Sciences, Division of Translational Toxicology, Predictive Toxicology Branch, Durham, NC 27713, USA. ^[4]

关键词 Chemical toxicity Exposure assessment Feature weighting Genetic algorithm Machine learning Ordinal regression

DOI 10.1016/j.comtox.2023.100294

PMID 38872937

发布时间 2025-05-30

基金项目

ZIA ES103385/ImNIH/Intramural NIH HHS/United States

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Computational toxicology (Amsterdam, Netherlands)

2024年29卷

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Computational toxicology (Amsterdam, Netherlands)

2024年29卷

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Guided optimization of ToxPi model weights using a Semi-Automated approach.

Computational toxicology (Amsterdam, Netherlands)

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Guided optimization of ToxPi model weights using a Semi-Automated approach.

Computational toxicology (Amsterdam, Netherlands)

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Computational toxicology (Amsterdam, Netherlands)

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