Display Settings:

Items per page
We are sorry, but NCBI web applications do not support your browser and may not function properly. More information

Results: 6

1.
Figure 3

Figure 3. From: GIBA: a clustering tool for detecting protein complexes.

The performance of the algorithms concerning Acc_g metric.

Charalampos N Moschopoulos, et al. BMC Bioinformatics. 2009;10(Suppl 6):S11-S11.
2.
Figure 1

Figure 1. From: GIBA: a clustering tool for detecting protein complexes.

The main window of the GIBA tool.

Charalampos N Moschopoulos, et al. BMC Bioinformatics. 2009;10(Suppl 6):S11-S11.
3.
Figure 6

Figure 6. From: GIBA: a clustering tool for detecting protein complexes.

Impact of density and haircut operation parameters to geometrical accuracy metric.

Charalampos N Moschopoulos, et al. BMC Bioinformatics. 2009;10(Suppl 6):S11-S11.
4.
Figure 4

Figure 4. From: GIBA: a clustering tool for detecting protein complexes.

Impact of density and haircut operation parameters to the produced number of clusters.

Charalampos N Moschopoulos, et al. BMC Bioinformatics. 2009;10(Suppl 6):S11-S11.
5.
Figure 2

Figure 2. From: GIBA: a clustering tool for detecting protein complexes.

The percentage of successful predictions in respect to the MIPS recorded complexes of the algorithms tested.

Charalampos N Moschopoulos, et al. BMC Bioinformatics. 2009;10(Suppl 6):S11-S11.
6.
Figure 5

Figure 5. From: GIBA: a clustering tool for detecting protein complexes.

Impact of density and haircut operation parameters to the mean score of valid predicted complexes.

Charalampos N Moschopoulos, et al. BMC Bioinformatics. 2009;10(Suppl 6):S11-S11.

Display Settings:

Items per page

Supplemental Content

Recent activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...
Write to the Help Desk