Mar 272012
 

MEDUSA

:: DESCRIPTION

MEDUSA (Motif Element Detection Using Sequence Agglomeration) is an integrative method for learning motif models of transcription factor binding sites by incorporating promoter sequence and gene expression data. We use a modern large-margin machine learning approach, based on boosting, to enable feature selection from the high-dimensional search space of candidate binding sequences while avoiding overfitting.

::DEVELOPER

Leslie Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows /MacOsX
  • Matlab

:: DOWNLOAD

 MEDUSA

:: MORE INFORMATION

Citation

Learning regulatory programs that accurately predict differential expression with MEDUSA.
Kundaje A, Lianoglou S, Li X, Quigley D, Arias M, Wiggins CH, Zhang L, Leslie C.
Ann N Y Acad Sci. 2007 Dec;1115:178-202. Epub 2007 Oct 12.

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