Rowell Craig, Carpenter Mark, Lamartiniere Coral A
Department of Pharmacology and Toxicology, UAB Comprehensive Cancer, University of Alabama at Birmingham, Birmingham, AL 35294, USA.
J Proteome Res. 2005 Sep-Oct;4(5):1619-27. doi: 10.1021/pr0501261.
We propose a statistical method to model the underlying distribution of protein spot volumes in 2-D gels using a generalized model (GM). We apply this approach to discover mechanisms of chemical carcinogenesis in a rodent model. We generated 247 protein spots that were common to all gels (n = 18). Traditional statistical methods found 6.5% (13 out of 247) significant protein spots, our GM approach yielded a total of 53 (22.5%) differentially expressed protein spots.
我们提出了一种统计方法，使用广义模型（GM）对二维凝胶中蛋白质斑点体积的潜在分布进行建模。我们将此方法应用于在啮齿动物模型中发现化学致癌机制。我们生成了所有凝胶（n = 18）共有的247个蛋白质斑点。传统统计方法发现6.5%（247个中的13个）显著蛋白质斑点，我们的GM方法共产生了53个（22.5%）差异表达蛋白质斑点。
