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Table 8 Accuracy and running time by different algorithms on Human and Yeast datasets using Human complexes and Yeast complexes as standard complexes

From: Identifying protein complexes based on an edge weight algorithm and core-attachment structure

Dataset Algorithms PC F-measure MMR CR Running time/s
Human PEWCC 2930 0.39552nd 0.09632nd 0.5155 83.05 s 2nd
  COACH 4484 0.2455 0.0677 0.5408 1 st 2851 s
  ProRank+ 838 0.3651 0.0687 0.2856 282.66 s
  EWCA 1979 0.4048 1 st 0.0964 1 st 0.52212nd 29.37 s 1 st
Yeast PEWCC 1353 0.3446 2nd 0.0871 2nd 0.4946 36.58 s 2nd
  COACH 1547 0.2083 0.0466 0.5520 2nd 3603.31 s
  ProRank+ 513 0.2712 0.0487 0.2816 251.54 s
  EWCA 924 0.4199 1 st 0.0982 1 st 0.6182 1 st 18.54 s 1 st
  1. As the table shows, EWCA obtains best F-measure, MMR and Running time in all the two datasets. Given the results of F-measure, it shows the accuracy of protein complexes identified by EWCA is better than these comparison algorithms. The results of Running time, it is said the efficient of EWCA is faster than those algorithms. In a word, EWCA could both accuracy and efficient than some state-of-the-art algorithms with having a higher accuracy according to Tables 3 and 4. NOTE: The highest value in each row is shown in bold
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