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Open Access Highly Accessed Research article

Identification of gene interactions associated with disease from gene expression data using synergy networks

John Watkinson1, Xiaodong Wang1, Tian Zheng2 and Dimitris Anastassiou1*

Author Affiliations

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

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BMC Systems Biology 2008, 2:10  doi:10.1186/1752-0509-2-10

Published: 30 January 2008

Additional 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.

Format: PDF Size: 21KB Download file

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