APA (7th ed.) Citation

NJ, D., DP, R., E, C., X, Q., & H, Z. (2024). Predicting Chemical Immunotoxicity through Data-Driven QSAR Modeling of Aryl Hydrocarbon Receptor Agonism and Related Toxicity Mechanisms. Environment & health (Washington, D.C.), 2(7), 474. https://doi.org/10.1021/envhealth.4c00026

Chicago Style (17th ed.) Citation

NJ, Daood, Russo DP, Chung E, Qin X, and Zhu H. "Predicting Chemical Immunotoxicity Through Data-Driven QSAR Modeling of Aryl Hydrocarbon Receptor Agonism and Related Toxicity Mechanisms." Environment & Health (Washington, D.C.) 2, no. 7 (2024): 474. https://doi.org/10.1021/envhealth.4c00026.

MLA (9th ed.) Citation

NJ, Daood, et al. "Predicting Chemical Immunotoxicity Through Data-Driven QSAR Modeling of Aryl Hydrocarbon Receptor Agonism and Related Toxicity Mechanisms." Environment & Health (Washington, D.C.), vol. 2, no. 7, 2024, p. 474, https://doi.org/10.1021/envhealth.4c00026.