Bipartite network analysis reveals metabolic gene expression profiles that are highly associated with the clinical outcomes of acute myeloid leukemia
作者: Fanfan XieMingxiong HeLi HeKeqin LiuMenglong LiGuoquan HuZhining Wen
作者单位: 1College of Chemistry, Sichuan University, Chengdu, Sichuan, China
2Biomass Energy Technology Research Center, Biogas Institute of Ministry of Agriculture, Chengdu, Sichuan, China
3Biogas Appliance Quality Supervision and Inspection Center, Biogas Institute of Ministry of Agriculture, Chengdu, Sichuan, China
刊名: Computational Biology and Chemistry, 2017
来源数据库: Elsevier Journal
DOI: 10.1016/j.compbiolchem.2017.01.002
关键词: Metabolic genesGene expression profilesBipartite networkAcute myeloid leukemiaSurvival analysis
原始语种摘要: Abstract(#br)Dysregulated and reprogrammed metabolism is one of the most important characteristics of cancer, and exploiting cancer cell metabolism can aid in understanding the diverse clinical outcomes for patients. To investigate the differences in metabolic pathways among patients with acute myeloid leukemia (AML) and differential survival outcomes, we systematically conducted microarray data analysis of the metabolic gene expression profiles from 384 patients available from the Gene Expression Omnibus and Cancer Genome Atlas databases. Pathway enrichment analysis of differentially expressed genes (DEGs) showed that the metabolic differences between low-risk and high-risk patients mainly existed in two pathways: biosynthesis of unsaturated fatty acids and oxidative phosphorylation....
全文获取路径: Elsevier  (合作)
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影响因子:1.793 (2012)

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