Daood, Nada J, Russo, Daniel P, Chung, Elena, Qin, Xuebin, and Zhu, Hao. Predicting Chemical Immunotoxicity through Data-Driven QSAR Modeling of Aryl Hydrocarbon Receptor Agonism and Related Toxicity Mechanisms. Retrieved from https://par.nsf.gov/biblio/10530163. Environment & Health 2.7 Web. doi:10.1021/envhealth.4c00026.

Daood, Nada J, Russo, Daniel P, Chung, Elena, Qin, Xuebin, & Zhu, Hao. Predicting Chemical Immunotoxicity through Data-Driven QSAR Modeling of Aryl Hydrocarbon Receptor Agonism and Related Toxicity Mechanisms. Environment & Health, 2 (7). Retrieved from https://par.nsf.gov/biblio/10530163. https://doi.org/10.1021/envhealth.4c00026

Daood, Nada J, Russo, Daniel P, Chung, Elena, Qin, Xuebin, and Zhu, Hao. "Predicting Chemical Immunotoxicity through Data-Driven QSAR Modeling of Aryl Hydrocarbon Receptor Agonism and Related Toxicity Mechanisms". Environment & Health 2 (7). Country unknown/Code not available: American Chemical Society. https://doi.org/10.1021/envhealth.4c00026. https://par.nsf.gov/biblio/10530163.

@article{osti_10530163,
place = {Country unknown/Code not available}, title = {Predicting Chemical Immunotoxicity through Data-Driven QSAR Modeling of Aryl Hydrocarbon Receptor Agonism and Related Toxicity Mechanisms}, url = {https://par.nsf.gov/biblio/10530163}, DOI = {10.1021/envhealth.4c00026}, abstractNote = {}, journal = {Environment & Health}, volume = {2}, number = {7}, publisher = {American Chemical Society}, author = {Daood, Nada J and Russo, Daniel P and Chung, Elena and Qin, Xuebin and Zhu, Hao}, }