Disease-related gene search by association analysis based on link structure

2006 ◽  
Vol 37 (5) ◽  
pp. 46-55
Author(s):  
Tsutomu Matsunaga
Keyword(s):  
Association Analysis ◽  
Related Gene ◽  
Link Structure ◽  
Gene Search ◽  
Disease Related Gene

Transcriptional impact of resminostat and other HDAC inhibitors on disease-related gene expression in CTCL

2019 ◽  
Vol 119 ◽  
pp. S10
Author(s):  
A.C. Bretz ◽  
G. Streubel ◽  
U. Parnitzke ◽  
M. Borgmann ◽  
S. Hamm
Keyword(s):  
Gene Expression ◽  
Hdac Inhibitors ◽  
Related Gene ◽  
Disease Related Gene

scholarly journals Cryopreservation of microglia enables single-cell RNA sequencing with minimal effects on disease-related gene expression patterns

iScience ◽  
2021 ◽  
Vol 24 (4) ◽  
pp. 102357
Author(s):  
Brenda Morsey ◽  
Meng Niu ◽  
Shetty Ravi Dyavar ◽  
Courtney V. Fletcher ◽  
Benjamin G. Lamberty ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Related Gene ◽  
Single Cell Rna Sequencing ◽  
Disease Related Gene

Thyroid Hormone Up-Regulates an Alzheimer Disease–Related Gene Seladin-1 at the Transcriptional Level

2011 ◽  
pp. OR30-3-OR30-3 ◽  
Author(s):  
Emi Ishida ◽  
Koshi Hashimoto ◽  
Atsushi Ozawa ◽  
Nobuyuki Shibusawa ◽  
Tetsurou Satoh ◽  
...  
Keyword(s):  
Thyroid Hormone ◽  
Alzheimer Disease ◽  
Transcriptional Level ◽  
Related Gene ◽  
Disease Related Gene

scholarly journals Gene Targeting of a Disease-Related Gene in Human Induced Pluripotent Stem and Embryonic Stem Cells

2009 ◽  
Vol 5 (1) ◽  
pp. 97-110 ◽  
Author(s):  
Jizhong Zou ◽  
Morgan L. Maeder ◽  
Prashant Mali ◽  
Shondra M. Pruett-Miller ◽  
Stacey Thibodeau-Beganny ◽  
...  
Keyword(s):  
Stem Cells ◽  
Embryonic Stem Cells ◽  
Gene Targeting ◽  
Embryonic Stem ◽  
Related Gene ◽  
Induced Pluripotent ◽  
Disease Related Gene

scholarly journals Differentially Coexpressed Disease Gene Identification Based on Gene Coexpression Network

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Xue Jiang ◽  
Han Zhang ◽  
Xiongwen Quan
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Gene Selection ◽  
Coexpression Network ◽  
Expression Data ◽  
Gene Coexpression Network ◽  
Related Gene ◽  
Differential Coexpression ◽  
Gene Coexpression ◽  
Disease Related Gene

Screening disease-related genes by analyzing gene expression data has become a popular theme. Traditional disease-related gene selection methods always focus on identifying differentially expressed gene between case samples and a control group. These traditional methods may not fully consider the changes of interactions between genes at different cell states and the dynamic processes of gene expression levels during the disease progression. However, in order to understand the mechanism of disease, it is important to explore the dynamic changes of interactions between genes in biological networks at different cell states. In this study, we designed a novel framework to identify disease-related genes and developed a differentially coexpressed disease-related gene identification method based on gene coexpression network (DCGN) to screen differentially coexpressed genes. We firstly constructed phase-specific gene coexpression network using time-series gene expression data and defined the conception of differential coexpression of genes in coexpression network. Then, we designed two metrics to measure the value of gene differential coexpression according to the change of local topological structures between different phase-specific networks. Finally, we conducted meta-analysis of gene differential coexpression based on the rank-product method. Experimental results demonstrated the feasibility and effectiveness of DCGN and the superior performance of DCGN over other popular disease-related gene selection methods through real-world gene expression data sets.

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