Table 1.
Overview of subcellular localization prediction programs for eukaryotic proteins
| Classification method | Number of localization sites | Accuracy |
|
BaCelLo [14] http://gpcr.biocomp.unibo.it/bacello/ |
4-5 | 67-76% |
|
LOCtree [15] http://cubic.bioc.columbia.edu/services/loctree/ |
4 | 74% |
|
MITOPRED [16] http://bioapps.rit.albany.edu/MITOPRED/ |
1 | 85% |
|
MultiLoc [17] http://www-bs.informatik.uni-tuebingen.de/Services/MultiLoc/ |
11 | 75% |
|
PA-SUB [18] http://www.cs.ualberta.ca/~bioinfo/PA/Sub/ |
11 | 81-94% |
|
pTarget [19,20] http://bioapps.rit.albany.edu/pTARGET/ |
9 | 68-87% |
|
TargetP [21] http://www.cbs.dtu.dk/services/TargetP/ |
3 | 90% |
|
WoLF PSORT [22] http://wolfpsort.org/ |
12 | 80% |
A selection of subcellular localization prediction programs for eukaryotic proteins reported to have a medium to high prediction accuracy. Listed are the numbers of compartments each program can predict targeting to, and the reported accuracy of the prediction.