Matrix factorization for recovery of biological processes from microarray data.
Matrix factorization for recovery of biological processes from microarray data.
复制标题
DOI：
10.1016/s0076-6879(09)67003-8
复制
发表时间：
2009
影响因子：
--
通讯作者：
Ochs, Michael F.
中科院分区：
文献类型：
--
作者：
Kossenkov, Andrew V.;Ochs, Michael F.
我们探索了一些矩阵分解方法，他们的能力，以确定在一个大型的基因表达研究的生物过程的签名。我们专注于这些方法的能力，找到签名的基因本体增强和解释这些签名的样本。两种贝叶斯方法，贝叶斯分解（BD）和贝叶斯因子回归建模（BFRM），表现最好。样品之间的签名强度的差异表明，BD将是最有用的系统建模和生物标志物发现的BFRM。
We explore a number of matrix factorization methods in terms of their ability to identify signatures of biological processes in a large gene expression study. We focus on the ability of these methods to find signatures in terms of gene ontology enhancement and on the interpretation of these signatures in the samples. Two Bayesian approaches, Bayesian Decomposition (BD) and Bayesian Factor Regression Modeling (BFRM), perform best. Differences in the strength of the signatures between the samples suggest that BD will be most useful for systems modeling and BFRM for biomarker discovery.