Telomere length and chromosomal instability for predicting individual radiosensitivity and risk via machine learning

MLA

Miles J. McKenna, et al. Telomere Length and Chromosomal Instability for Predicting Individual Radiosensitivity and Risk via Machine Learning. Mar. 2020. EBSCOhost, https://doi.org/10.1101/2020.03.27.009043.

APA

Miles J. McKenna, Susan M. Bailey, Aidan M. Lewis, Jared J. Luxton, S.G. Jhavar, Gregory P. Swanson, & Lynn Taylor. (2020). Telomere length and chromosomal instability for predicting individual radiosensitivity and risk via machine learning. https://doi.org/10.1101/2020.03.27.009043

Chicago

Miles J. McKenna, Susan M. Bailey, Aidan M. Lewis, Jared J. Luxton, S.G. Jhavar, Gregory P. Swanson, and Lynn Taylor. 2020. “Telomere Length and Chromosomal Instability for Predicting Individual Radiosensitivity and Risk via Machine Learning,” March. doi:10.1101/2020.03.27.009043.