APA (7th ed.) Citation

Almufarriji, F. M., Ajmal, A., Alotaibi, B. S., Alamri, M. A., Khalid, A., & Wadood, A. (2024). Subtractive genomics integrated with deep learning, molecular docking, and MD simulation decipher therapeutic drug targets and their potential inhibitors against Nocardia farcinica strain IFM 10152. Chemical Papers, 78(18), 9435. https://doi.org/10.1007/s11696-024-03755-1

Chicago Style (17th ed.) Citation

Almufarriji, Fawaz M., Amar Ajmal, Bader S. Alotaibi, Mubarak A. Alamri, Asaad Khalid, and Abdul Wadood. "Subtractive Genomics Integrated with Deep Learning, Molecular Docking, and MD Simulation Decipher Therapeutic Drug Targets and Their Potential Inhibitors Against Nocardia Farcinica Strain IFM 10152." Chemical Papers 78, no. 18 (2024): 9435. https://doi.org/10.1007/s11696-024-03755-1.

MLA (9th ed.) Citation

Almufarriji, Fawaz M., et al. "Subtractive Genomics Integrated with Deep Learning, Molecular Docking, and MD Simulation Decipher Therapeutic Drug Targets and Their Potential Inhibitors Against Nocardia Farcinica Strain IFM 10152." Chemical Papers, vol. 78, no. 18, 2024, p. 9435, https://doi.org/10.1007/s11696-024-03755-1.