Supplementary Methods from State-Transition Analysis of Time-Sequential Gene Expression Identifies Critical Points That Predict Development of Acute Myeloid Leukemia

MLA

Guido Marcucci, et al. Supplementary Methods from State-Transition Analysis of Time-Sequential Gene Expression Identifies Critical Points That Predict Development of Acute Myeloid Leukemia. Mar. 2023. EBSCOhost, https://doi.org/10.1158/0008-5472.22426282.v1.

APA

Guido Marcucci, Ya-Huei Kuo, Nadia Carlesso, Stephen Forman, Leo D. Wang, Zheng Liu, Yate-Ching Yuan, Xiwei Wu, Davide Maestrini, Herman Wu, Ayelet Marom, Lianjun Zhang, Emily Carnahan, Guerry Cook, Wei-Kai Hua, Denis O’Meally, David E. Frankhouser, Jing Qi, Sergio Branciamore, & Russell C. Rockne. (2023). Supplementary Methods from State-Transition Analysis of Time-Sequential Gene Expression Identifies Critical Points That Predict Development of Acute Myeloid Leukemia. https://doi.org/10.1158/0008-5472.22426282.v1

Chicago

Guido Marcucci, Ya-Huei Kuo, Nadia Carlesso, Stephen Forman, Leo D. Wang, Zheng Liu, Yate-Ching Yuan, et al. 2023. “Supplementary Methods from State-Transition Analysis of Time-Sequential Gene Expression Identifies Critical Points That Predict Development of Acute Myeloid Leukemia,” March. doi:10.1158/0008-5472.22426282.v1.