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Predicting the Probability that a Chemical Causes Steatosis Using Adverse Outcome Pathway Bayesian Networks (AOPBNs).

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Title: Predicting the Probability that a Chemical Causes Steatosis Using Adverse Outcome Pathway Bayesian Networks (AOPBNs).
Authors: Burgoon LD; US Army Engineer Research and Development Center, Vicksburg, MS, USA., Angrish M; US Environmental Protection Agency, National Center for Environmental Assessment, Research Triangle Park, NC, USA., Garcia-Reyero N; US Army Engineer Research and Development Center, Vicksburg, MS, USA., Pollesch N; US Environmental Protection Agency, Mid-Continent Ecology Division, Duluth, MN, USA., Zupanic A; Eawag, Swiss Federal Institute for Aquatic Science and Technology, Dubendorf, Switzerland., Perkins E; US Army Engineer Research and Development Center, Vicksburg, MS, USA.
Source: Risk analysis : an official publication of the Society for Risk Analysis [Risk Anal] 2020 Mar; Vol. 40 (3), pp. 512-523. Date of Electronic Publication: 2019 Nov 13.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Blackwell Publishers Country of Publication: United States NLM ID: 8109978 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1539-6924 (Electronic) Linking ISSN: 02724332 NLM ISO Abbreviation: Risk Anal Subsets: MEDLINE
Database: MEDLINE Ultimate
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PubType: Academic Journal
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  Data: Predicting the Probability that a Chemical Causes Steatosis Using Adverse Outcome Pathway Bayesian Networks (AOPBNs).
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  Data: <searchLink fieldCode="AU" term="%22Burgoon+LD%22">Burgoon LD</searchLink>; US Army Engineer Research and Development Center, Vicksburg, MS, USA.<br /><searchLink fieldCode="AU" term="%22Angrish+M%22">Angrish M</searchLink>; US Environmental Protection Agency, National Center for Environmental Assessment, Research Triangle Park, NC, USA.<br /><searchLink fieldCode="AU" term="%22Garcia-Reyero+N%22">Garcia-Reyero N</searchLink>; US Army Engineer Research and Development Center, Vicksburg, MS, USA.<br /><searchLink fieldCode="AU" term="%22Pollesch+N%22">Pollesch N</searchLink>; US Environmental Protection Agency, Mid-Continent Ecology Division, Duluth, MN, USA.<br /><searchLink fieldCode="AU" term="%22Zupanic+A%22">Zupanic A</searchLink>; Eawag, Swiss Federal Institute for Aquatic Science and Technology, Dubendorf, Switzerland.<br /><searchLink fieldCode="AU" term="%22Perkins+E%22">Perkins E</searchLink>; US Army Engineer Research and Development Center, Vicksburg, MS, USA.
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  Data: <searchLink fieldCode="JN" term="%228109978%22">Risk analysis : an official publication of the Society for Risk Analysis</searchLink> [Risk Anal] 2020 Mar; Vol. 40 (3), pp. 512-523. <i>Date of Electronic Publication: </i>2019 Nov 13.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Blackwell+Publishers%22">Blackwell Publishers </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>8109978 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1539-6924 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2202724332%22">02724332 </searchLink><i>NLM ISO Abbreviation: </i>Risk Anal <i>Subsets: </i>MEDLINE
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        Value: 10.1111/risa.13423
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        Text: English
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              Text: 2020 Mar
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