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Predicting Chemical Immunotoxicity through Data-Driven QSAR Modeling of Aryl Hydrocarbon Receptor Agonism and Related Toxicity Mechanisms.

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Title: Predicting Chemical Immunotoxicity through Data-Driven QSAR Modeling of Aryl Hydrocarbon Receptor Agonism and Related Toxicity Mechanisms.
Authors: Daood NJ; Department of Chemistry and Biochemistry, Rowan University, Glassboro, New Jersey 08028, United States., Russo DP; Department of Chemistry and Biochemistry, Rowan University, Glassboro, New Jersey 08028, United States., Chung E; Department of Chemistry and Biochemistry, Rowan University, Glassboro, New Jersey 08028, United States.; Center for Biomedical Informatics and Genomics, Tulane University School of Medicine, New Orleans, Louisiana 70112, United States., Qin X; Tulane National Primate Research Center, Tulane University School of Medicine, Covington, Louisiana 70433, United States., Zhu H; Department of Chemistry and Biochemistry, Rowan University, Glassboro, New Jersey 08028, United States.; Center for Biomedical Informatics and Genomics, Tulane University School of Medicine, New Orleans, Louisiana 70112, United States.
Source: Environment & health (Washington, D.C.) [Environ Health (Wash)] 2024 May 28; Vol. 2 (7), pp. 474-485. Date of Electronic Publication: 2024 May 28 (Print Publication: 2024).
Publication Type: Journal Article
Journal Info: Publisher: American Chemical Society Country of Publication: United States NLM ID: 9918646069906676 Publication Model: eCollection Cited Medium: Internet ISSN: 2833-8278 (Electronic) Linking ISSN: 28338278 NLM ISO Abbreviation: Environ Health (Wash) Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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  Data: Predicting Chemical Immunotoxicity through Data-Driven QSAR Modeling of Aryl Hydrocarbon Receptor Agonism and Related Toxicity Mechanisms.
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  Data: <searchLink fieldCode="AU" term="%22Daood+NJ%22">Daood NJ</searchLink>; Department of Chemistry and Biochemistry, Rowan University, Glassboro, New Jersey 08028, United States.<br /><searchLink fieldCode="AU" term="%22Russo+DP%22">Russo DP</searchLink>; Department of Chemistry and Biochemistry, Rowan University, Glassboro, New Jersey 08028, United States.<br /><searchLink fieldCode="AU" term="%22Chung+E%22">Chung E</searchLink>; Department of Chemistry and Biochemistry, Rowan University, Glassboro, New Jersey 08028, United States.; Center for Biomedical Informatics and Genomics, Tulane University School of Medicine, New Orleans, Louisiana 70112, United States.<br /><searchLink fieldCode="AU" term="%22Qin+X%22">Qin X</searchLink>; Tulane National Primate Research Center, Tulane University School of Medicine, Covington, Louisiana 70433, United States.<br /><searchLink fieldCode="AU" term="%22Zhu+H%22">Zhu H</searchLink>; Department of Chemistry and Biochemistry, Rowan University, Glassboro, New Jersey 08028, United States.; Center for Biomedical Informatics and Genomics, Tulane University School of Medicine, New Orleans, Louisiana 70112, United States.
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  Data: <searchLink fieldCode="JN" term="%229918646069906676%22">Environment & health (Washington, D.C.)</searchLink> [Environ Health (Wash)] 2024 May 28; Vol. 2 (7), pp. 474-485. <i>Date of Electronic Publication: </i>2024 May 28 (<i>Print Publication: </i>2024).
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        Value: 10.1021/envhealth.4c00026
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        Text: English
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      – TitleFull: Predicting Chemical Immunotoxicity through Data-Driven QSAR Modeling of Aryl Hydrocarbon Receptor Agonism and Related Toxicity Mechanisms.
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