# A Special Structural Based Weighted Network Approach for the Analysis of Protein Complexes
## 5 Results and Discussion
### Function Enrichment Analysis
\begin{table}
\begin{tabular}{c l l l l l l l l} \hline \hline
**Dataset** & **Algorithm** & \(\mathbf{C_{p}(v)}\) & **F-Measure** & **CR** & **MMR** & **Sep** & **ACC** &
\begin{tabular}{c} **CPU Run** \\ **Time (s)** \\ \end{tabular} \\ \hline Human & MCL & 315 & 0.1001 & 0.1759 & 0.0105 & 0.1753 & 0.2167 & 5906.34 \\  & COACH & 4484 & 0.2455 & 0.5408 & 0.0677 & 0.5216 & 0.2777 & 2851.05 \\  & EWCA & 1979 & 0.4048 & 0.5221 & 0.0964 & 0.6081 & 0.5221 & 29.37 \\  & CFinder & 449 & 0.1256 & 0.2834 & 0.0116 & 0.3912 & 0.2511 & 3896.35 \\  & GMFTP & 773 & 0.2651 & 0.4193 & 0.0419 & 0.4917 & 0.3852 & 254.67 \\  & Core & 576 & 0.1621 & 0.3267 & 0.1267 & 0.3573 & 0.2778 & 2853.14 \\  & CALM & 1108 & 0.5127 & 0.5182 & 0.1394 & 0.6894 & 0.5289 & 198.39 \\  & ClusterONE & 375 & 0.1026 & 0.3071 & 0.0207 & 0.3773 & 0.2975 & 4895.78 \\  & CMC & 672 & 0.1251 & 0.2503 & 0.0183 & 0.2975 & 0.3313 & 3904.83 \\  & ProRank+ & 838 & 0.3651 & 0.2856 & 0.0687 & 0.5526 & 0.5613 & 282.66 \\  & WECALM & 2367 & 0.4255 & 0.5155 & 0.0981 & 0.6155 & 0.6219 & 28.45 \\ \hline Yeast & MCL & 298 & 0.1104 & 0.2761 & 0.0117 & 0.1625 & 0.1395 & 4967.47 \\  & COACH & 1551 & 0.2083 & 0.5521 & 0.0466 & 0.3583 & 0.3117 & 3603.31 \\  & EWCA & 936 & 0.4199 & 0.6182 & 0.0982 & 0.5904 & 0.5879 & 18.54 \\  & CFinder & 351 & 0.1429 & 0.2749 & 0.0281 & 0.3453 & 0.4163 & 3432.07 \\  & GMFTP & 675 & 0.2763 & 0.3129 & 0.0309 & 0.5145 & 0.4092 & 229.89 \\  & Core & 402 & 0.2124 & 0.2968 & 0.3285 & 0.1517 & 0.3218 & 2543.34 \\  & CALM & 732 & 0.4015 & 0.6787 & 0.1433 & 0.6261 & 0.6532 & 154.89 \\  & ClusterONE & 317 & 0.2012 & 0.2767 & 0.0285 & 0.3371 & 0.3255 & 3989.92 \\  & CMC & 589 & 0.2115 & 0.1975 & 0.0198 & 0.2934 & 0.3553 & 2987.63 \\  & ProRank+ & 516 & 0.2712 & 0.2816 & 0.0487 & 0.5471 & 0.5602 & 251.54 \\  & WECALM & 1891 & 0.4216 & 0.6394 & 0.0487 & 0.64131 & 0.6534 & 17.65 \\ \hline \hline \end{tabular} \(\mathbf{C_{p}(r)}\): Detected Protein Complex; **CR**: Coverage Rate ; **MMR**: Maximum Match Ratio ; **Sep**: Separation ; **ACC**: Geometrical Mean Accuracy.  
\end{table} 
Table 3: An evaluation of computational complexity and accuracy of WECALM and other algorithms. CFinder, and GMFTP discovered far fewer protein complexes than WECALM. Nevertheless, when compared to the WECALM method, they had a lower percentage of significant protein complexes. In terms of the total number of detected protein complexes and the percentage of detected complexes, WECALM outperformed the other methods in terms of functionality and biological significance. According to their \(p\)-value, these protein complexes detected by WECALM have a higher probability of being actual protein complexes. The WECALM detected five protein complexes with extremely low \(p\)-values using the BioGRID and DIP complex datasets, as shown in Appendix B (see Tables A3 and A4), to further validate the biological significance of the identified complexes. The Cluster frequency, Genome frequency, Biological Process \(p\)-values, False Discovery Rate (FDR), False Positive score value, and Gene Ontology term descriptions were all evaluated in our analysis. Cluster frequency is a metric employed in the evaluation of algorithms designed to detect protein complexes. It represents the number of times the algorithm detects a specific complex across several replicates or runs of a similar test. In Table A3 in Appendix B we can see that WECALM detected protein complexes with a high cluster frequency on the BioGRID complexes. A high cluster frequency implies that the WECALM detects a protein complex consistently throughout multiple runs, implying a good performance. This also means that most of the detected protein complexes in the BioGRID dataset closely match the gene ontology term and have a functional relationship with high statistical significance. According to results in Table A4, WECALM detected protein complexes with a high cluster frequency on the DIP complexes a clear indication of good performance.