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Table 1 Results of BiCluE on artificial graphs with a varying numbers of vertices.

From: BiCluE - Exact and heuristic algorithms for weighted bi-cluster editing of biomedical data

No. of Vertices

No. of Edges

Costs

Running Times(s)

  

FP.

EDH.

FP.

EDH.

10

[12,14]

23.786

25.575

0.0514

0.0704

20

[31,73]

114.024

114.934

0.0940

0.320

25

[42,101]

106.902

116.36

5.061

0.318

30

[74,190]

197.510

209.9

275.336

1.626

35

[126,170]

339.941

345.232

744.231

5.212

40

[144.326]

437.44

454.713

2183.653

6.578

50

[185,468]

(--)

652.204

(--)

40.601

60

[266,635]

(--)

943.902

(--)

260.957

70

[430,740]

(--)

1397.101

(--)

376.010

80

[632,1341]

(--)

1784.506

(--)

711.245

90

[936,1679]

(--)

2243.770

(--)

1670.032

  1. Costs and running times are averaged over 5 runs. For graphs with ≤ 40 vertices, we applied both algorithms. For graphs with > 40 vertices, the fixed-parameter algorithm cannot finish within reasonable time. Hence, we only report the performance of the edge deletion heuristics. Better costs and running times are marked with bold font. Abbreviations: FP: fixed-parameter algorithm; EDH: edge deletion heuristics