Dynamic Regulatory Events Miner (DREM)
DREM map of heat 
shock response in yeast

The Dynamic Regulatory Events Miner (DREM) allows one to model, analyze, and visualize transcriptional gene regulation dynamics. The method of DREM takes as input time series gene expression data and static or dynamic transcription factor-gene interaction data (e.g. ChIP-chip data), and produces as output a dynamic regulatory map. The dynamic regulatory map highlights major bifurcation events in the time series expression data and transcription factors potentially responsible for them. See the manual and papers below for more details.

  • NEW!!! mirDREM was just released. mirDREM supports the use of microRNAs in DREM
    allowing for dynamic models that integrate both TFs and miRNAs
    when reconstructing dynamic regulatory networks. You can read more about it at the following reference:

    M. H. Schulz, K.V. Pandit, C.L. Lino Cardenasb, N. Ambalavanan, N. Kaminski, and Z. Bar-Joseph.
    Reconstructing dynamic microRNA-regulated interaction networks
    Proceedings of the National Academy of Sciences of the United States of America (PNAS), , doi: 10.1073/pnas, 2013

  • DREM 2.0 was released and supports a number of new features including (see manual for details):
    - new static binding data for mouse, human, D. melanogaster, A. thaliana
    - a new and more flexible implementation of the IOHMM supports dynamic binding data for each time point or as a mix of static/dynamic TF input
    - expression levels of TFs can be used to improve the models learned by DREM
    - the motif finder DECOD can be used in conjuction with DREM and help find DNA motifs for unannotated splits
    - new features for the visualization of expressed TFs, dragging boxes in the model view, and switching between representations

  • Click here to download DREM version 2.0 (versionlog.txt)
  • DREM User manual: DREMmanual.pdf
  • The DREM method was originally described and applied to yeast in the paper: J. Ernst, O. Vainas, C.T. Harbison, I. Simon, and Z. Bar-Joseph. Reconstructing Dynamic Regulatory Maps. Nature-EMBO Molecular Systems Biology, 3:74, 2007. Click here for Supporting Information specific to that paper
  • If you use the DREM 2.0 and beyond please cite also: M.H. Schulz, W.E. Devanny, A. Gitter, S. Zhong, J. Ernst and Z. Bar-Joseph
    DREM 2.0: Improved reconstruction of dynamic regulatory networks from time-series expression data, BMC Systems Biology 2012
  • Other examples of published papers using DREM as part of the data analysis can be found here.
  • Email any questions, comments, or bugs found to Jason Ernst (jernst@cs.cmu.edu) or Marcel Schulz (maschulz@cs.cmu.edu)

  • Short Primer: Starting DREM
    1. To run DREM Java 1.5 or higher must be installed
    2. Save the drem.zip file to a computer.
    3. Unzip the drem.zip file
    4a. If on windows double click on the .cmd file corresponding to the condition of interest to see DREM opened with the data from that condition.
    4b. If not on windows start DREM from the drem directory with the command java -mx1024M -ms512M -jar drem.jar -d [defaultfilename] where defaultfilename is the name of the condition DREM should be opened with. For instance to open DREM with the heat shock data type java -mx1024M -ms512M -jar drem.jar -d defaultsHeatSample.txt
    If you want to use a human dataset try java -mx1024M -ms512M -jar drem.jar -d defaultsHumanSample.txt

    Using DREM
    5. Once DREM is open press the execute button at the bottom.
    6. To see only genes assigned to a certain path click on that path.
    7. The gene table button displays the names of the genes currently display by DREM.
    8. The GO table displays a GO enrichment for all genes displayed by DREM

    Please read the provided manual to learn more about the features of DREM!

    The development of DREM, DREM2.0 and mirDREM was supported in part by NIH grants NO1 AI-5001, 1R01GM085022 and U01HL108642 and NSF CAREER award 0448453 to ZBJ