Cite
Unraveling pathogenesis, biomarkers and potential therapeutic agents for endometriosis associated with disulfidptosis based on bioinformatics analysis, machine learning and experiment validation.
MLA
Zhao, Xiaoxuan, et al. “Unraveling Pathogenesis, Biomarkers and Potential Therapeutic Agents for Endometriosis Associated with Disulfidptosis Based on Bioinformatics Analysis, Machine Learning and Experiment Validation.” Journal of Biological Engineering, vol. 18, no. 1, July 2024, pp. 1–24. EBSCOhost, https://doi.org/10.1186/s13036-024-00437-0.
APA
Zhao, X., Zhao, Y., Zhang, Y., Fan, Q., Ke, H., Chen, X., Jin, L., Tang, H., Jiang, Y., & Ma, J. (2024). Unraveling pathogenesis, biomarkers and potential therapeutic agents for endometriosis associated with disulfidptosis based on bioinformatics analysis, machine learning and experiment validation. Journal of Biological Engineering, 18(1), 1–24. https://doi.org/10.1186/s13036-024-00437-0
Chicago
Zhao, Xiaoxuan, Yang Zhao, Yuanyuan Zhang, Qingnan Fan, Huanxiao Ke, Xiaowei Chen, Linxi Jin, Hongying Tang, Yuepeng Jiang, and Jing Ma. 2024. “Unraveling Pathogenesis, Biomarkers and Potential Therapeutic Agents for Endometriosis Associated with Disulfidptosis Based on Bioinformatics Analysis, Machine Learning and Experiment Validation.” Journal of Biological Engineering 18 (1): 1–24. doi:10.1186/s13036-024-00437-0.