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GOTermViewer: Visualization of Gene Ontology Enrichment in Multiple Differential Gene Expression Analyses
by
Carr, Ian M
, Hull, Mark
, Volpato, Milene
in
Biological effects
/ Biological properties
/ Developmental biology
/ Enrichment
/ Gene expression
/ Genes
/ Method and Protocol
/ Ontology
/ Physiology
2024
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GOTermViewer: Visualization of Gene Ontology Enrichment in Multiple Differential Gene Expression Analyses
by
Carr, Ian M
, Hull, Mark
, Volpato, Milene
in
Biological effects
/ Biological properties
/ Developmental biology
/ Enrichment
/ Gene expression
/ Genes
/ Method and Protocol
/ Ontology
/ Physiology
2024
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Do you wish to request the book?
GOTermViewer: Visualization of Gene Ontology Enrichment in Multiple Differential Gene Expression Analyses
by
Carr, Ian M
, Hull, Mark
, Volpato, Milene
in
Biological effects
/ Biological properties
/ Developmental biology
/ Enrichment
/ Gene expression
/ Genes
/ Method and Protocol
/ Ontology
/ Physiology
2024
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GOTermViewer: Visualization of Gene Ontology Enrichment in Multiple Differential Gene Expression Analyses
Journal Article
GOTermViewer: Visualization of Gene Ontology Enrichment in Multiple Differential Gene Expression Analyses
2024
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Overview
Gene ontology phrases are a widely used set of hierarchical terms that describe the biological properties of genes. These terms are then used to annotate individual genes, making it possible to determine the likely physiological properties of groups of genes such as a list of differentially expressed genes. Consequently, their ability to predict changes in biological features and functions based on alterations in gene expression has made gene ontology terms popular in the wide range of bioinformatic fields, such as differential gene expression and evolutionary biology. However, while they make the analysis easier, it is seldom easy to convey the results in a readily understandable manner. A number of applications have been developed to visualize gene ontology (GO) term enrichment; however, these solutions tend to focus on the display of aggregated results from a single analysis, making them unsuitable for the analysis of a series of experiments such as a time course or response to different drug treatments. As multiple pair wise comparisons are becoming a common feature of RNA profiling experiments, the absence of a mechanism to easily compare them is a significant problem. Consequently, to overcome this obstacle, we have developed GOTermViewer, an application that displays GO term enrichment data as determined by GOstats such that changes in physiological response across a number of individual analyses across a time course or range of drug treatments can be visualized.
Publisher
SAGE Publications,Sage Publications Ltd,SAGE Publishing
Subject
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