APA (7th ed.) Citation

E, S., L, O., H, T., & S, D. (2024). Developing Dynamic Structure-Based Pharmacophore and ML-Trained QSAR Models for the Discovery of Novel Resistance-Free RET Tyrosine Kinase Inhibitors Through Extensive MD Trajectories and NRI Analysis. ChemMedChem, 19(12), e202300644. https://doi.org/10.1002/cmdc.202300644

Chicago Style (17th ed.) Citation

E, Sayyah, Oktay L, Tunc H, and Durdagi S. "Developing Dynamic Structure-Based Pharmacophore and ML-Trained QSAR Models for the Discovery of Novel Resistance-Free RET Tyrosine Kinase Inhibitors Through Extensive MD Trajectories and NRI Analysis." ChemMedChem 19, no. 12 (2024): e202300644. https://doi.org/10.1002/cmdc.202300644.

MLA (9th ed.) Citation

E, Sayyah, et al. "Developing Dynamic Structure-Based Pharmacophore and ML-Trained QSAR Models for the Discovery of Novel Resistance-Free RET Tyrosine Kinase Inhibitors Through Extensive MD Trajectories and NRI Analysis." ChemMedChem, vol. 19, no. 12, 2024, p. e202300644, https://doi.org/10.1002/cmdc.202300644.