scholarly journals Differential Coexpression Analysis Reveals Extensive Rewiring of Arabidopsis Gene Coexpression in Response to Pseudomonas syringae Infection

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Zhenhong Jiang ◽  
Xiaobao Dong ◽  
Zhi-Gang Li ◽  
Fei He ◽  
Ziding Zhang
Keyword(s):  
Pseudomonas Syringae ◽  
Arabidopsis Gene ◽  
Coexpression Analysis ◽  
Differential Coexpression ◽  
Gene Coexpression ◽  
Differential Coexpression Analysis

scholarly journals Gene differential coexpression analysis based on biweight correlation and maximum clique

2014 ◽  
Vol 15 (Suppl 15) ◽  
pp. S3 ◽  
Author(s):  
Chun-Hou Zheng ◽  
Lin Yuan ◽  
Wen Sha ◽  
Zhan-Li Sun
Keyword(s):  
Maximum Clique ◽  
Coexpression Analysis ◽  
Differential Coexpression ◽  
Differential Coexpression Analysis

scholarly journals Differential coexpression analysis of obesity-associated networks in human subcutaneous adipose tissue

2011 ◽  
Vol 36 (1) ◽  
pp. 137-147 ◽  
Author(s):  
A J Walley ◽  
P Jacobson ◽  
M Falchi ◽  
L Bottolo ◽  
J C Andersson ◽  
...  
Keyword(s):  
Adipose Tissue ◽  
Subcutaneous Adipose Tissue ◽  
Coexpression Analysis ◽  
Differential Coexpression ◽  
Differential Coexpression Analysis ◽  
Subcutaneous Adipose

scholarly journals SUBSPACE DIFFERENTIAL COEXPRESSION ANALYSIS:

2009 ◽  
pp. 145-156 ◽  
Author(s):  
GANG FANG ◽  
RUI KUANG ◽  
GAURAV PANDEY ◽  
MICHAEL STEINBACH ◽  
CHAD L. MYERS ◽  
...  
Keyword(s):  
Coexpression Analysis ◽  
Differential Coexpression ◽  
Differential Coexpression Analysis

scholarly journals Module Based Differential Coexpression Analysis Method for Type 2 Diabetes

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Lin Yuan ◽  
Chun-Hou Zheng ◽  
Jun-Feng Xia ◽  
De-Shuang Huang
Keyword(s):  
Type 2 Diabetes ◽  
Differential Expression Analysis ◽  
Maximum Clique ◽  
Analysis Method ◽  
Threshold Strategy ◽  
Coexpression Analysis ◽  
Differential Coexpression ◽  
Differential Coexpression Analysis ◽  
Gene Modules

More and more studies have shown that many complex diseases are contributed jointly by alterations of numerous genes. Genes often coordinate together as a functional biological pathway or network and are highly correlated. Differential coexpression analysis, as a more comprehensive technique to the differential expression analysis, was raised to research gene regulatory networks and biological pathways of phenotypic changes through measuring gene correlation changes between disease and normal conditions. In this paper, we propose a gene differential coexpression analysis algorithm in the level of gene sets and apply the algorithm to a publicly available type 2 diabetes (T2D) expression dataset. Firstly, we calculate coexpression biweight midcorrelation coefficients between all gene pairs. Then, we select informative correlation pairs using the “differential coexpression threshold” strategy. Finally, we identify the differential coexpression gene modules using maximum clique concept andk-clique algorithm. We apply the proposed differential coexpression analysis method on simulated data and T2D data. Two differential coexpression gene modules about T2D were detected, which should be useful for exploring the biological function of the related genes.

scholarly journals Combining differential expression and differential coexpression analysis identifies optimal gene and gene set in cervical cancer

2018 ◽  
Vol 14 (1) ◽  
pp. 201 ◽  
Author(s):  
Hong-Bing Cai ◽  
Sheng-Quan Fang ◽  
Min Gao ◽  
Shi-Lu Xiong ◽  
Hai-Yan Chen ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Differential Expression ◽  
Coexpression Analysis ◽  
Gene Set ◽  
Differential Coexpression ◽  
Differential Coexpression Analysis

scholarly journals Differential coexpression analysis using microarray data and its application to human cancer

2005 ◽  
Vol 21 (24) ◽  
pp. 4348-4355 ◽  
Author(s):  
J. K. Choi ◽  
U. Yu ◽  
O. J. Yoo ◽  
S. Kim
Keyword(s):  
Microarray Data ◽  
Human Cancer ◽  
Coexpression Analysis ◽  
Differential Coexpression ◽  
Differential Coexpression Analysis

scholarly journals Gene Coexpression Analysis in Single Cells Indicates Lymphomyeloid Copriming in Short-Term Hematopoietic Stem Cells and Multipotent Progenitors

2010 ◽  
Vol 184 (9) ◽  
pp. 4907-4917 ◽  
Author(s):  
Laetitia Gautreau ◽  
Amine Boudil ◽  
Valérie Pasqualetto ◽  
Lamia Skhiri ◽  
Laure Grandin ◽  
...  
Keyword(s):  
Stem Cells ◽  
Hematopoietic Stem Cells ◽  
Single Cells ◽  
Short Term ◽  
Hematopoietic Stem ◽  
Coexpression Analysis ◽  
Gene Coexpression ◽  
Multipotent Progenitors
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