Signaling pathway impact analysis by incorporating the importance and specificity of genes (SPIA-IS). (December 2017)

• Record Type: Journal Article
• Authors: Fang, Hongyuan; Li, Xianbin; Zan, Xiangzhen; Shen, Liangzhong; Ma, Runnian; Liu, Wenbin
• Is Part Of: Computational biology and chemistry. Volume 71(2017)
• Page Start: 236
• Page End: 244
• Publication Date: 2017-12
• Subjects: Gene expression profile -- Signaling pathway analysis -- Gene importance -- Gene specificity; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2017.09.009
• Languages: English
• ISSNs: 1476-9271

Abstract

Abstract: rlying biology of differentially expressed genes and proteins. Although various approaches have been proposed to identify cancer-related pathways, most of them only partially consider the influence of those differentially expressed genes, such as the gene numbers, their perturbation in the signaling transduction, and the interaction between genes. Signaling-pathway impact analysis (SPIA) provides a convenient framework which considers both the classical enrichment analysis and the actual perturbation on a given pathway. In this study, we extended previous proposed SPIA by incorporating the importance and specificity of genes (SPIA-IS). We applied this approach to six datasets for colorectal cancer, lung cancer, and pancreatic cancer. Results from these datasets showed that the proposed SPIA-IS could effectively improve the performance of the original SPIA in identifying cancer-related pathways.