Research article
Identification of gene interactions associated with disease from gene expression data using synergy networks
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* Corresponding author: Dimitris Anastassiou anastas@ee.columbia.edu
1 Center for Computational Biology and Bioinformatics and Department of Electrical Engineering, Columbia University, 500 West 120th Street, New York, NY 10027, USA
2 Department of Statistics, Columbia University, 1255 Amsterdam Avenue, New York, NY 10027, USA
BMC Systems Biology 2008, 2:10 doi:10.1186/1752-0509-2-10
Published: 30 January 2008Additional files
Additional file 1:
Example with simulated dataset. Comparison between using synergy networks and traditional network inference techniques on a simulated dataset.
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Additional file 2:
Synergy values in validation dataset. Results of applying the synergy network algorithm on an independent dataset used for validation.
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Additional file 3:
Software for evaluating entropy and synergy. MATLAB scripts are provided for evaluating conditional entropy and synergy from gene expression data and a corresponding phenotype indicator.
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