Bio-Computing Research Center, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, China.
Comput Biol Med. 2012 May;42(5):582-9. doi: 10.1016/j.compbiomed.2012.02.002. Epub 2012 Feb 24.
Sparse methods have a significant advantage to reduce the complexity of genes expression data and to make them more comprehensible and interpretable. In this paper, based on penalized matrix decomposition (PMD), a novel approach is proposed to extract plants core genes, i.e., the characteristic gene set, responding to abiotic stresses. Core genes can capture the changes of the samples. In other words, the features of samples can be caught by the core genes. The experimental results show that the proposed PMD-based method is efficient to extract the core genes closely related to the abiotic stresses.
稀疏方法具有显著的优势，可以降低基因表达数据的复杂性，使其更易于理解和解释。在本文中，基于惩罚矩阵分解（PMD），提出了一种新的方法来提取植物核心基因，即响应非生物胁迫的特征基因集。核心基因可以捕捉样本的变化。换句话说，核心基因可以捕获样本的特征。实验结果表明，所提出的基于 PMD 的方法能够有效地提取与非生物胁迫密切相关的核心基因。
