Using Protein-Protein Interactions for Refining Gene Networks Estimated from Microarray Data by Bayesian Networks
Using Protein-Protein Interactions for Refining Gene Networks Estimated from Microarray Data by Bayesian Networks
复制标题
DOI：
10.1142/9789812704856_0032
复制
发表时间：
2003-12
影响因子：
--
通讯作者：
Naoki Nariai;SunYong Kim;S. Imoto;S. Miyano
中科院分区：
文献类型：
--
作者：
Naoki Nariai;SunYong Kim;S. Imoto;S. Miyano
我们提出了一种从DNA微阵列数据和蛋白质-蛋白质相互作用中估计基因网络的统计方法。由于蛋白质或多蛋白质复合体之间的物理相互作用可能调节生物过程，仅使用mRNA表达数据不足以准确估计基因网络。我们的方法将蛋白质-蛋白质相互作用的知识添加到贝叶斯统计框架下的基因网络估计方法中。在估计的基因网络中，基于主成分分析将蛋白质复合体建模为虚拟节点。通过对酿酒酵母细胞周期数据的分析，验证了该方法的有效性。该方法提高了估计基因网络的准确性，并成功地识别了一些生物事实。
We propose a statistical method to estimate gene networks from DNA microarray data and protein-protein interactions. Because physical interactions between proteins or multiprotein complexes are likely to regulate biological processes, using only mRNA expression data is not sufficient for estimating a gene network accurately. Our method adds knowledge about protein-protein interactions to the estimation method of gene networks under a Bayesian statistical framework. In the estimated gene network, a protein complex is modeled as a virtual node based on principal component analysis. We show the effectiveness of the proposed method through the analysis of Saccharomyces cerevisiae cell cycle data. The proposed method improves the accuracy of the estimated gene networks, and successfully identifies some biological facts.