Short Time-series Expression Miner (STEM). 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.)

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References in zbMATH (referenced in 4 articles )

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  1. Passos, Valéria Lima; Tan, Frans E. S.; Berger, Martijn P. F.: Cost-efficiency considerations in the choice of a microarray platform for time course experimental designs (2011)
  2. Sinha, Anshu; Markatou, Marianthi: A platform for processing expression of short time series (PESTS) (2011) ioport
  3. Antoniotti, Marco; Carreras, Marco; Farinaccio, Antonella; Mauri, Giancario; Merico, Daniele; Zoppis, Italo: An application of kernel methods to gene cluster temporal meta-analysis (2010)
  4. Ernst, Jason; Bar-Joseph, Ziv: STEM: a tool for the analysis of short time series gene expression data (2006) ioport