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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