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Your search keyword '"Fangming Fu"' showing total 2 results
Start Over Author "Fangming Fu" Topic gene expression
2 results on '"Fangming Fu"'

1. Bioinformatic analysis of specific genes in diabetic nephropathy

Author

Nianrong Mi, Xueling Wei, Fangming Fu, and Jinbo Liu

Subjects
Genetics, ACTG1, Databases, Factual, Gene Expression Profiling, Computational Biology, Down-Regulation, General Medicine, Biology, Critical Care and Intensive Care Medicine, medicine.disease, Up-Regulation, Pathogenesis, Diabetic nephropathy, Vascular endothelial growth factor A, Differentially expressed genes, Nephrology, Ppi network, Gene expression, Linear Models, medicine, Humans, Diabetic Nephropathies, Gene, Oligonucleotide Array Sequence Analysis
Abstract

We attempt to explore the pathogenesis and specific genes with aberrant expression in diabetic nephropathy (DN).The gene expression profile of GSE1009 was downloaded from Gene Expression Omnibus database, including 3 normal function glomeruli and DN glomeruli from cadaveric donor kidneys. The differentially expressed genes (DEGs) were analyzed and the aberrant gene-related functions were predicted by informatics methods. The protein-protein interaction (PPI) networks for DEGs were constructed and the functional sub-network was screened.A total of 416 DEGs were found to be differentially expressed in DN samples comparing with normal controls, including 404 up-regulated genes and 12 down-regulated genes. DEGs were involved in the process of combination to saccharides and the decline of tissue repairing ability of the organisms. The genes of VEGFA, ACTG1, HSP90AA1 had high degree in the PPI network. The main biological process of genes in the sub-network was related with cell proliferation and signal transmitting of cell membrane receptor.Significant nodes in PPI network provide new insights to understand the mechanism of DN. VEGFA, ACTG1 and HSP90AA1 may be the potential targets in the DN treatment.

Published
2015
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2. An insight into the key genes and biological functions associated with insulin resistance in adipose tissue with microarray technology.

Author

LI ZHANG, YING CUI, FANGMING FU, ZHENZUO LI, XIAOXIA PAN, HONGZHUAN LI, and LIN LI

Subjects
INSULIN resistance, DIABETES, ADIPOSE tissues, MICROARRAY technology, GENE expression
Abstract

In the present study, the key genes and biological functions associated with insulin resistance were investigated by comparing the gene expression profiles of adipose tissue obtained from insulin-sensitive and insulin-resistant patients. The gene expression data set GSE20950 was downloaded from the Gene Expression Omnibus, including 39 adipose tissue samples obtained from insulin-sensitive and insulin-resistant patients undergoing gastric bypass surgery. Adipose samples were divided into two groups (the insulin-sensitive and insulin-resistant groups) and the differentially expressed genes (DEGs) were screened out with packages of R. The interactions among DEGs were retrieved with Osprey and functional enrichment analysis was performed with the WebGestalt system. Information regarding the interaction network and enriched biological functions was combined to construct a functional interaction network. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was then conducted using the Database for Annotation, Visualization and Integrated Discovery. A total of 170 DEGs were detected in the insulin-sensitive group, 8 downregulated and 162 upregulated. Response to glucose stimulus was the most significantly over-represented functional term. The focal adhesion pathway was identified to be significant in the genes of the functional interaction network. The present study revealed key biological functions and DEGs in adipose tissues associated with insulin resistance, which may facilitate the development of novel therapies for insulin resistance and diabetes. [ABSTRACT FROM AUTHOR]

Published
2015
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