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/ webcite

4-5

67-76%

LOCtree [15]

http://cubic.bioc.columbia.edu/services/loctree/ webcite

4

74%

MITOPRED [16]

http://bioapps.rit.albany.edu/MITOPRED/ webcite

1

85%

MultiLoc [17]

http://www-bs.informatik.uni-tuebingen.de/Services/MultiLoc/ webcite

11

75%

PA-SUB [18]

http://www.cs.ualberta.ca/~bioinfo/PA/Sub/ webcite

11

81-94%

pTarget [19,20]

http://bioapps.rit.albany.edu/pTARGET/ webcite

9

68-87%

TargetP [21]

http://www.cbs.dtu.dk/services/TargetP/ webcite

3

90%

WoLF PSORT [22]

http://wolfpsort.org/ webcite

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.

Desler et al. BMC Bioinformatics 2009 10:289   doi:10.1186/1471-2105-10-289

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