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GoMiner is a tool for biological interpretation of 'omic' data – including data from gene expression microarrays. Omic experiments often generate lists of dozens or hundreds of genes that differ in expression between samples, raising the question
What does it all mean biologically?
To answer this question, GoMiner leverages the Gene Ontology (GO) to identify the biological processes, functions and components represented in these lists. Instead of analyzing microarray results with a gene-by-gene approach, GoMiner classifies the genes into biologically coherent categories and assesses these categories. The insights gained through GoMiner can generate hypotheses to guide additional research.
We have updated our Getting Started section with guidance on chosing between GoMiner and High-Throughput GoMiner
To get started using GoMiner
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We would like to hear from you. You can reach the team via email.
GoMiner was originally developed jointly by the Genomics and Bioinformatics Group (GBG) of LMP, NCI, NIH and the Medical Informatics and Bioimaging group of BME, Georgia Tech/Emory University. It is now maintained and under continuing development by GBG.
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