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Genetics and Genomics Commons

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Philadelphia College of Osteopathic Medicine

Gene identification

Publication Year

Articles 1 - 2 of 2

Full-Text Articles in Genetics and Genomics

Egonet: Identification Of Human Disease Ego-Network Modules, Rendong Yang, Yun Bai, Zhaohui Qin, Tianwei Yu Jan 2014

Egonet: Identification Of Human Disease Ego-Network Modules, Rendong Yang, Yun Bai, Zhaohui Qin, Tianwei Yu

PCOM Scholarly Papers

Background: Mining novel biomarkers from gene expression profiles for accurate disease classification is challenging due to small sample size and high noise in gene expression measurements. Several studies have proposed integrated analyses of microarray data and protein-protein interaction (PPI) networks to find diagnostic subnetwork markers. However, the neighborhood relationship among network member genes has not been fully considered by those methods, leaving many potential gene markers unidentified. The main idea of this study is to take full advantage of the biological observation that genes associated with the same or similar diseases commonly reside in the same neighborhood of molecular networks.Results: …


Genome-Wide Expression Analysis In Down Syndrome: Insight Into Immunodeficiency, Chong Li, Lei Jin, Yun Bai, Qimin Chen, Lijun Fu, Minjun Yang, Huasheng Xiao, Guoping Zhao, Shengyue Wang Jan 2012

Genome-Wide Expression Analysis In Down Syndrome: Insight Into Immunodeficiency, Chong Li, Lei Jin, Yun Bai, Qimin Chen, Lijun Fu, Minjun Yang, Huasheng Xiao, Guoping Zhao, Shengyue Wang

PCOM Scholarly Papers

Down syndrome (DS) is caused by triplication of Human chromosome 21 (Hsa21) and associated with an array of deleterious phenotypes, including mental retardation, heart defects and immunodeficiency. Genome-wide expression patterns of uncultured peripheral blood cells are useful to understanding of DS-associated immune dysfunction. We used a Human Exon microarray to characterize gene expression in uncultured peripheral blood cells derived from DS individuals and age-matched controls from two age groups: neonate (N) and child (C). A total of 174 transcript clusters (gene-level) with eight located on Hsa21 in N group and 383 transcript clusters including 56 on Hsa21 in C group …