SBC logo Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden.

NucPred

Fetching O70133 from www.uniprot.org...

The NucPred score for your sequence is 0.53 (see score help below)

   1  MGDIKNFLYAWCGKRKMTPAYEIRAVGNKNRQKFMCEVRVEGFNYAGMGN    50
  51  STNKKDAQSNAARDFVNYLVRINEVKSEEVPAVGIVPPPPILSDTSDSTA   100
 101  SAAEGLPAPMGGPLPPHLALKAEENNSGVESSGYGSPGPTWDRGANLKDY   150
 151  YSRKEEQEVQATLESEEVDLNAGLHGNWTLENAKARLNQYFQKEKIQGEY   200
 201  KYTQVGPDHNRSFIAEMTIYIKQLGRRIFAREHGSNKKLAAQSCALSLVR   250
 251  QLYHLGVIEAYSGLTKKKEGERVEPYKVFLSPDLELQLQNVVQELDLEIV   300
 301  PPPVDPSMPVILNIGKLAHFEPSQRQNAVGVVPWSPPQSNWNPWTSSNID   350
 351  EGPLAYASTEQISMDLKNELTYQMEQDHNLQSVLQERELLPVKKFEAEIL   400
 401  EAISSNSVVIIRGATGCGKTTQVPQYILDDFIQNDRAAECNIVVTQPRRI   450
 451  SAVAVAERVAYERGEEPGKSCGYSVRFESILPRPHASIMFCTVGVLLRKL   500
 501  EAGIRGISHVIVDEIHERDINTDFLLVVLRDVVLAYPEVRIVLMSATIDT   550
 551  TMFCEYFFNCPIIEVYGRTFPVQEYFLEDCIQMTQFIPPPKDKKKKDKED   600
 601  DGGEDDDANCNLICGDEYGPETKLSMSQLNEKETPFELIEALLKYIETLN   650
 651  VPGAVLVFLPGWNLIYTMQKHLENNSHFGSHRYQILPLHSQIPREEQRKV   700
 701  FDPVPDGVTKVILSTNIAETSITINDVVYVIDSCKQKVKLFTAHNNMTNY   750
 751  ATVWASKTNLEQRKGRAGRVRPGFCFHLCSRARFDRLETHMTPEMFRTPL   800
 801  HEIALSIKLLRLGGIGQFLAKAIEPPPLDAIIEAEHTLRELDALDANDEL   850
 851  TPLGRILAKLPIEPRFGKMMIMGCIFYVGDAVCTISAATCFPEPFISEGK   900
 901  RLGYIHRNFAGNRFSDHVALLSVFQAWDDARMSGEEAEIRFCEQKRLNMA   950
 951  TLRMTWEAKVQLKEILINSGFPEDCLLTQVFTNTGPDNNLDVVISLLAFG  1000
1001  VYPNVCYHKEKRKILTTEGRNALIHKSSVNCPFSSQDMKYPSPFFVFGEK  1050
1051  IRTRAISAKGMTLVTPLQLLLFASKKVQSDGQIVFIDDWIRLQISHEAAA  1100
1101  CITIRAAMEALVVEVSKQPNIISQLDPVNEHMLNTIRQISRPSAAGINLM  1150
1151  IGSVRYGDGPRPPKMARYDNGSGYRRGYGGGGYGGGGYGGGYGSGGFGGG  1200
1201  FGSGGGFGGGFNSGGGGFGSGGGGFGSGGGGFGGGGGGFSGGGGGGFGGG  1250
1251  RGGGGGGFGGSGGFGNGGGGYGVGGGGYGGGGGGGYGGGSGGYGGGGYGG  1300
1301  GEGYSISPNSYRGNYGGGGGGYRGGSQGGYRNNFGGDYRGSSGDYRGSGG  1350
1351  GYRGSGGFQRRGYGGGYFGQGRGGGGGGGY                      1380

Positively and negatively influencing subsequences are coloured according to the following scale:

(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)

with NucPred



If you find NucPred useful, please cite this paper:
NucPred - Predicting Nuclear Localization of Proteins. Brameier M, Krings A, Maccallum RM. Bioinformatics, 2007. PubMed id: 17332022
The authors also look forward to your comments and suggestions.

What does the NucPred score mean?

You have to decide on a NucPred score threshold. Sequences which score greater than or equal to this threshold are predicted to spend some time in the nucleus. Higher thresholds yield fewer predicted nuclear proteins, but these predictions are more accurate (you can have higher confidence in them). The table below gives more details of the performance of NucPred estimated using the sequences it was trained on (by cross-validation). Another benchmark is available in the Bioinformatics 2007 paper.

NucPred score threshold Specificity Sensitivity
see above fraction of proteins predicted to be nuclear that actually are nuclear fraction of true nuclear proteins that are predicted (coverage)
0.10 0.45 0.88
0.20 0.52 0.83
0.30 0.57 0.77
0.40 0.63 0.69
0.50 0.70 0.62
0.60 0.71 0.53
0.70 0.81 0.44
0.80 0.84 0.32
0.90 0.88 0.21
1.00 1.00 0.02

Sequences which score >= 0.8 with NucPred and which are predicted by PredictNLS to contain an NLS have been shown to be 93% correct with a coverage of 16%. (PredictNLS by itself is 87% correct with 26% coverage on the same data.)

Go back to the NucPred Home Page.