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We have previously developed GoMiner, a program that organizes lists of 'interesting' genes (for example, under- and overexpressed genes from a microarray experiment) for biological interpretation in the context of the Gene Ontology. High-Throughput GoMiner is an enhancement of GoMiner which efficiently performs the computationally-challenging task of automated batch processing of an arbitrary number of microarray experiments. High-Throughput GoMiner is implemented with both a command line interface and a web interface.When should you use High-Throughput GoMiner?
High-Throughput GoMiner can also be useful if you want to have the performance benefit of co-locating GoMiner and its companion database, but do not want to set up your own local database.
A description of the relationship of this new version of the tool and the original version is available.
Example of a Clustered Image Map of Categories in a Time Series
Generated with High-Throughput GoMiner and CIMminer.
Thanks to Eldad Elnekave, Danielle M Hari, and Thomas A Wynn for the data used to generate the image.
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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