APA (7th ed.) Citation

Liu, Y., Bai, F., Tang, Z., Liu, N., & Liu, Q. (2021). Integrative transcriptomic, proteomic, and machine learning approach to identifying feature genes of atrial fibrillation using atrial samples from patients with valvular heart disease. BMC cardiovascular disorders, 21(1), 52-10. https://doi.org/10.1186/s12872-020-01819-0

Chicago Style (17th ed.) Citation

Liu, Yaozhong, Fan Bai, Zhenwei Tang, Na Liu, and Qiming Liu. "Integrative Transcriptomic, Proteomic, and Machine Learning Approach to Identifying Feature Genes of Atrial Fibrillation Using Atrial Samples from Patients with Valvular Heart Disease." BMC Cardiovascular Disorders 21, no. 1 (2021): 52-10. https://doi.org/10.1186/s12872-020-01819-0.

MLA (9th ed.) Citation

Liu, Yaozhong, et al. "Integrative Transcriptomic, Proteomic, and Machine Learning Approach to Identifying Feature Genes of Atrial Fibrillation Using Atrial Samples from Patients with Valvular Heart Disease." BMC Cardiovascular Disorders, vol. 21, no. 1, 2021, pp. 52-10, https://doi.org/10.1186/s12872-020-01819-0.