Fuzzy soft subspace clustering method for gene co-expression network analysis
Fuzzy soft subspace clustering method for gene co-expression network analysis
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DOI：
10.1007/s13042-015-0486-7
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发表时间：
2016-01
影响因子：
5.6
通讯作者：
Qiang Wang;Guoliang Chen
中科院分区：
文献类型：
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作者：
Qiang Wang;Guoliang Chen
用于构建基因共表达网络的基因表达聚类方法受到细胞生物学复杂性的极大影响。 本文提出了一种模糊软子空间聚类方法，用于检测可能参与多种细胞过程并具有不同生物学功能的局部共表达基因的重叠簇。该方法可以提取基因簇的子空间和基因簇之间的相互作用，为基因共表达网络分析提供有用的信息。在酵母细胞周期基准微阵列数据上的实验表明，该方法能够有效地提取基因间潜在的生物学关系，增强基因共表达网络的推理能力。
Gene expression clustering methods for building gene co-expression networks suffer greatly from the biological complexity of cells. This paper proposes a fuzzy soft subspace clustering method for detecting overlapped clusters of locally co-expressed genes that may participate in multiple cellular processes and take on different biological functions. Process-specific cluster subspaces and interactions among different gene clusters can be extracted by this method, providing useful information for gene co-expression networks analysis. Experiments on the yeast cell cycle benchmark microarray data have shown that this method is effective in extracting underlying biological relationships between genes, and enhancing gene co-expression network inference.