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URL: http://www.cs.cmu.edu/~jernst/stem/
Proper Citation: Short Time-series Expression Miner (STEM) (RRID:SCR_005016)
Description: The Short Time-series Expression Miner (STEM) is a Java program for clustering, comparing, and visualizing short time series gene expression data from microarray experiments (~8 time points or fewer). STEM allows researchers to identify significant temporal expression profiles and the genes associated with these profiles and to compare the behavior of these genes across multiple conditions. STEM is fully integrated with the Gene Ontology (GO) database supporting GO category gene enrichment analyses for sets of genes having the same temporal expression pattern. STEM also supports the ability to easily determine and visualize the behavior of genes belonging to a given GO category or user defined gene set, identifying which temporal expression profiles were enriched for these genes. (Note: While STEM is designed primarily to analyze data from short time course experiments it can be used to analyze data from any small set of experiments which can naturally be ordered sequentially including dose response experiments.) Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Abbreviations: STEM
Synonyms: Short Time-series Expression Miner
Resource Type: data processing software, software resource, software application
Defining Citation: PMID:16597342, PMID:15961453
Keywords: statistical analysis, term enrichment, visualization, cluster, compare, short time series, gene expression, microarray, expression profile, gene, gene ontology, gene enrichment analyses, FASEB list
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The NIDDK Information Network (dkNET) serves the needs of basic and clinical investigators by providing seamless access to large pools of data and research resources relevant to the mission of The National Institute of Diabetes Digestive and Kidney Diseases (NIDDK). dkNET is hosted at University of California San Diego, and is supported by NIH NIDDK grant 2U24DK097771-09.
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