Lee Seungmook, Jhun Mina, Lee Eun-Kyung, Park Taesung
Department of Statistics, Seoul National University, San 56-1, Sillim-dong, Gwanak-gu, Seoul 151-742, Korea.
BMC Proc. 2007;1 Suppl 1(Suppl 1):S76. doi: 10.1186/1753-6561-1-s1-s76. Epub 2007 Dec 18.
Understanding the genetic basis of human variation is an important goal of biomedical research. In this study, we used structural equation models (SEMs) to construct genetic networks to model how specific single-nucleotide polymorphisms (SNPs) from two genes known to cause acute myeloid leukemia (AML) by somatic mutation, runt-related transcription factor 1 (RUNX1) and ets variant gene 6 (ETV6), affect expression levels of other genes and how RUNX1 and ETV6 are related to each other. The SEM approach allows us to compare several candidate models from which an explanatory genetic network can be constructed.
了解人类变异的遗传基础是生物医学研究的一个重要目标。在本研究中,我们使用结构方程模型(SEM)构建遗传网络,以模拟已知通过体细胞突变导致急性髓系白血病(AML)的两个基因—— runt相关转录因子1(RUNX1)和ets变异基因6(ETV6)中的特定单核苷酸多态性(SNP)如何影响其他基因的表达水平,以及RUNX1和ETV6如何相互关联。SEM方法使我们能够比较几个候选模型,从中构建一个解释性遗传网络。