 Methodology articleModifying the DPClus algorithm for identifying protein complexes based on new topological structuresMin Li1 1 School of Information Science and Engineering, Central South University, Changsha, Hunan 410083, PR China 2 Department of Computer Science, Texas A&M University, College Station, Texas 77843, USA
BMC Bioinformatics 2008, 9:398doi:10.1186/1471-2105-9-398
Additional filesAdditional file 1: P-values for the predicted clusters with size ≥ 6 generated using Tin = 0.9 and Tin = 0.6. The data provided represent the statistical analysis of the predicted clusters. P-value is calculated for each predicted cluster and a function category is assigned to it when the minimum P-value occurs. When Tin = 0.9, there are 132 clusters (size ≥ 6) generated by IPCA. When Tin = 0.6, there are 443 clusters (size ≥ 6) generated by IPCA. Format: XLS Size: 168KB Download file This file can be viewed with: Microsoft Excel Viewer Additional file 2: Functional annotation for a predicted cluster of 10 proteins. This file provides a cluster which is composed of ten proteins: YGL173c, YOL149w, YBL026w, YCR077c, YJR022w, YER112w, YER146w, YDR378c, YNL147w, and YLR438c-a. The functional annotations for each protein in the cluster are listed in this file. Format: DOC Size: 47KB Download file This file can be viewed with: Microsoft Word Viewer |
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