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.)

  • The Short Time-series Expression Miner (STEM) version 1.3.13 (version log) is freely available under a GPL v3.0 license. Click here to download STEM.
  • STEM requires Java 1.4 or later to also be installed.
  • The user manual for STEM can be found here.
  • The STEM software is described in:
    J. Ernst, Z. Bar-Joseph. STEM: a tool for the analysis of short time series gene expression data.
    BMC Bioinformatics, 7:191, 2006.
  • STEM implements the clustering algorithm described in:
    J. Ernst, G.J. Nau, and Z. Bar-Joseph. Clustering Short Time Series Gene Expression Data.
    Bioinformatics (Proceedings of ISMB 2005), 21 Suppl. 1, pp. i159-i168, 2005. Supporting website.
  • Examples of published papers using STEM as part of the data analysis can be found here.
  • A short video showing screenshots of STEM can be found here (AVI, no audio, 15M).
  • Screenshots of the software with explanations are available here.
  • The ability of STEM to compare data sets from different experimental conditions is described with screenshots here and new options from version 1.2 can be found here.
  • Related software, the Dynamic Regulatory Events Miner (DREM), for modeling gene regulation dynamics can be found here.
  • Sign-up here for a google group mailing list to receive announcements of new versions of STEM and DREM (previous registrations have not been transferred to this list).
  • Email any questions or comments about STEM to Jason Ernst ( Click here for answers to frequently asked questions.
  • Source code is available on GitHub here.
  • Individuals contributing to the development of STEM are: Jason Ernst, Dima Patek, and Ziv Bar-Joseph
  • The interface of STEM makes use of the open source software Piccolo and Batik. The Piccolo and Batik libraries that STEM uses are included with the STEM download.
  • Funding for STEM was supported in part by NIH grant NO1 AI-5001 and NSF CAREER award 0448453 to ZBJ