Jan 242013
 

EDISA 1.0

:: DESCRIPTION

EDISA (Extended Dimension Iterative Signature Algorithm) is a novel probabilistic clustering approach for 3D gene-condition-time datasets. Based on mathematical definitions of gene expression modules, the EDISA samples initial modules from the dataset which are then refined by removing genes and conditions until they comply with the module definition. A subsequent extension step ensures gene and condition maximality. We applied the algorithm to a synthetic dataset and were able to successfully recover the implanted modules over a range of background noise intensities.

EDISA Online Version

::DEVELOPER

the Center for Bioinformatics Tübingen (Zentrum für Bioinformatik Tübingen, ZBIT).

:: SCREENSHOTS

EDISA

:: REQUIREMENTS

  • Linux/ WIndows
  • Matlab

:: DOWNLOAD

  EDISA

:: MORE INFORMATION

Citation

Jochen Supper, Martin Strauch, Dierk Wanke, Klaus Harter, Andreas Zell:
EDISA: extracting biclusters from multiple time-series of gene expression profiles
BMC Bioinformatics 2007, 8:334

184 views

Sorry, the comment form is closed at this time.