Network

Number of uSCCs (with number of nodes)

Algorithm


 
approximation with DLACCTI

TSA

DFT

 
[s]

TI corrections

remaining errors

[s]

[s]

Tcell

1 (33)

0.79

71

2

0.34

0.02

EGFR

1 (33)

1.18

183

1

0.61

0.26

Tcell+EGFR

2 (33, 33)

6.0 ± 0.04

879 ± 79

3 ± 0

3.1 ± 0.03

419 ± 82

Regulon DB

1 (30)

103

145

0

11.8

1.0

CA1 neuron

1 (154)

25

1869

43*

582*

2213*

Cancer signaling

4 (2, 2, 2, 445)

243

2161

n/a

>12 h

>12 h

 The running times for the different algorithms are shown and the quality of the approximation with DLACCTI is assessed. Also, the number of uSCCS in the networks together with the number of nodes that they contain is shown. In the column "TI corrections" the number of shorter paths that can be identified with transitive inference after having run DLACC is given. The "remaining errors" column shows how many shortest paths (after the TI step) differ in their length compared to the exact results delivered by TSA or DFT. When an algorithm ran longer than 12 hours it was considered impractical and terminated. Therefore, no exact results were determined for the cancer signaling network and consequently the quality of the approximation with DLACCTI cannot be given (*) For the CA1 neuron, the search depths in the twostep algorithm and in the exhaustive search were limited to length 18 to make calculations practicable. Therefore some paths may have been missed. The longest shortest path identified for this network with the DLACCTI is also of length 18. The computational environment is the same as in Table 1.