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.
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::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
- Linux/Windows /MacOsX
- Matlab
:: DOWNLOAD
:: 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.