  Methodology articleSemantic integration to identify overlapping functional modules in protein interaction networksYoung-Rae Cho1 1 Department of Computer Science and Engineering, State University of New York, Buffalo, NY, USA 2 Department of Pharmaceutical Science, State University of New York, Buffalo, NY, USA
BMC Bioinformatics 2007, 8:265doi:10.1186/1471-2105-8-265
Additional filesAdditional file 1: Modularization results of the networks weighted by semantic similarity. Ten different output sets of modules were generated by the flow-based algorithm. The input was the protein interaction network weighted by semantic similarity. To assess the accuracy of modules, the average f-measure and the average -log(p-value) were measured for each output set. Format: PDF Size: 61KB Download file This file can be viewed with: Adobe Acrobat Reader Additional file 2: Modularization results of the networks weighted by semantic interactivity. Ten different output sets of modules were generated by the flow-based algorithm. The input was the protein interaction network weighted by semantic interactivity. To assess the accuracy of modules, the average f-measure and the average -log(p-value) were measured for each output set. Format: PDF Size: 61KB Download file This file can be viewed with: Adobe Acrobat Reader |
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