Hubness of a gene and its association with survival time in (A) normal tissue, (B) ER+ tumor tissue and (C) ER- tumor tissue. Y-axis: -log10 (p-value) of a gene in the Cox model. X-axis: the number of edges connected to a gene. The gene set consists of 961 genes that are significant associated with survival time (p-values Methods).</p
<p>These genes were filtered for having strong, independent <i>cis</i>-eQTL (pairwise ) using the ad...
In recent years, there has been widespread interest and a large number of publications on the applic...
These are the gene-gene interaction networks obtained from gene expression microarray data in the pa...
Co-expression network analysis provides useful information for studying gene regulation in biologica...
Co-expression network analysis provides useful information for studying gene regulation in biologica...
Global genetic networks provide additional information for the analysis of human diseases, beyond th...
<p>The patient gene expression data and the survival information specified by followup times and e...
Discovering the regulation of cancer-related gene is of great importance in cancer biology. Transcri...
Conventional differential gene expression analysis by methods such as SAM (Chu et al., 2001), studen...
Motivation: The Cox proportional hazard models are widely used in the study of cancer survival. Howe...
Thesis (Ph.D.)--University of Washington, 2013The advent of high-dimensional biological data from te...
An important application of microarray technology is to relate gene expression profiles to various c...
International audienceAbstractBackgroundModeling survival oncological data has become a major challe...
In the study of transcriptional data for different groups (e.g. cancer types) it\u27s reasonable to ...
Graphical models provide a rich framework for summarizing the dependencies among variables. The grap...
<p>These genes were filtered for having strong, independent <i>cis</i>-eQTL (pairwise ) using the ad...
In recent years, there has been widespread interest and a large number of publications on the applic...
These are the gene-gene interaction networks obtained from gene expression microarray data in the pa...
Co-expression network analysis provides useful information for studying gene regulation in biologica...
Co-expression network analysis provides useful information for studying gene regulation in biologica...
Global genetic networks provide additional information for the analysis of human diseases, beyond th...
<p>The patient gene expression data and the survival information specified by followup times and e...
Discovering the regulation of cancer-related gene is of great importance in cancer biology. Transcri...
Conventional differential gene expression analysis by methods such as SAM (Chu et al., 2001), studen...
Motivation: The Cox proportional hazard models are widely used in the study of cancer survival. Howe...
Thesis (Ph.D.)--University of Washington, 2013The advent of high-dimensional biological data from te...
An important application of microarray technology is to relate gene expression profiles to various c...
International audienceAbstractBackgroundModeling survival oncological data has become a major challe...
In the study of transcriptional data for different groups (e.g. cancer types) it\u27s reasonable to ...
Graphical models provide a rich framework for summarizing the dependencies among variables. The grap...
<p>These genes were filtered for having strong, independent <i>cis</i>-eQTL (pairwise ) using the ad...
In recent years, there has been widespread interest and a large number of publications on the applic...
These are the gene-gene interaction networks obtained from gene expression microarray data in the pa...