APA (7th ed.) Citation

Qazi, S., Richardson, S., Potts, M., Myers, S., Saund, S., De, T., & Trieu, V. (2025). Bioinformatic Approach to Identify Potential TGFB2 -Dependent and Independent Prognostic Biomarkers for Ovarian Cancers Treated with Taxol. International Journal of Molecular Sciences, 26(24), 11900. https://doi.org/10.3390/ijms262411900

Chicago Style (17th ed.) Citation

Qazi, Sanjive, Stephen Richardson, Mike Potts, Scott Myers, Saran Saund, Tapas De, and Vuong Trieu. "Bioinformatic Approach to Identify Potential TGFB2 -Dependent and Independent Prognostic Biomarkers for Ovarian Cancers Treated with Taxol." International Journal of Molecular Sciences 26, no. 24 (2025): 11900. https://doi.org/10.3390/ijms262411900.

MLA (9th ed.) Citation

Qazi, Sanjive, et al. "Bioinformatic Approach to Identify Potential TGFB2 -Dependent and Independent Prognostic Biomarkers for Ovarian Cancers Treated with Taxol." International Journal of Molecular Sciences, vol. 26, no. 24, 2025, p. 11900, https://doi.org/10.3390/ijms262411900.