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

NucPred

Fetching P91875 from www.uniprot.org...

The NucPred score for your sequence is 0.74 (see score help below)

   1  MGSKRAMDVHMFPSDLEFAVFTDQEIRKLSVVKVITGITFDALGHAIPGG    50
  51  LYDIRMGSYGRCMDPCGTCLKLQDCPGHMGHIELGTPVYNPFFIKFVQRL   100
 101  LCIFCLHCYKLQMKDHECEIIMLQLRLIDAGYIIEAQELELFKSEIVCQN   150
 151  TENLVAIKNGDMVHPHIAAMYKLLEKNEKNSSNSTKTSCSLRTAITHSAL   200
 201  QRLGKKCRHCNKSMRFVRYMHRRLVFYVTLADIKERVGTGAETGGQNKVI   250
 251  FADECRRYLRQIYANYPELLKLLVPVLGLSNTDLTQGDRSPVDLFFMDTL   300
 301  PVTPPRARPLNMVGDMLKGNPQTDIYINIIENNHVLNVVLKYMKGGQEKL   350
 351  TEEAKAAYQTLKGETAHEKLYTAWLALQMSVDVLLDVNMSREMKSGEGLK   400
 401  QIIEKKSGLIRSHMMGKRVNYAARTVITPDPNINVDEIGIPDIFAKKLSY   450
 451  PVPVTEWNVTELRKMVMNGPDVHPGANYIQDKNGFTTYIPADNASKRESL   500
 501  AKLLLSNPKDGIKIVHRHVLNGDVLLLNRQPSLHKPSIMGHKARILHGEK   550
 551  TFRLHYSNCKAYNADFDGDEMNAHYPQSEVARAEAYNLVNVASNYLVPKD   600
 601  GTPLGGLIQDHVISGVKLSIRGRFFNREDYQQLVFQGLSQLKKDIKLLPP   650
 651  TILKPAVLWSGKQILSTIIINIIPEGYERINLDSFAKIAGKNWNVSRPRP   700
 701  PICGTNPEGNDLSESQVQIRNGELLVGVLDKQQYGATTYGLIHCMYELYG   750
 751  GDVSTLLLTAFTKVFTFFLQLEGFTLGVKDILVTDVADRKRRKIIRECRN   800
 801  VGNSAVAAALELEDEPPHDELVEKMEAAYVKDSKFRVLLDRKYKSLLDGY   850
 851  TNDINSTCLPRGLITKFPSNNLQLMVLSGAKGSMVNTMQISCLLGQIELE   900
 901  GKRPPLMISGKSLPSFTSFETSPKSGGFIDGRFMTGIQPQDFFFHCMAGR   950
 951  EGLIDTAVKTSRSGYLQRCLIKHLEGLSVHYDLTVRDSDNSVVQFLYGED  1000
1001  GLDILKSKFFNDKFCADFLTQNATAILRPAQLQLMKDEEQLAKVQRHEKH  1050
1051  IRSWEKKKPAKLRAAFTHFSEELREEVEVKRPNEINSKTGRRRFDEGLLK  1100
1101  LWKKADAEDKALYRKKYARCPDPTVAVYKQDLYYGSVSERTRKLITDYAK  1150
1151  RKPALKETIADIMRVKTIKSLAAPGEPVGLIAAQSIGEPSTQMTLNTFHF  1200
1201  AGRGEMNVTLGIPRLREILMLASSNIKTPSMDIPIKPGQQHQAEKLRINL  1250
1251  NSVTLANLLEYVHVSTGLTLDPERSYEYDMRFQFLPREVYKEDYGVRPKH  1300
1301  IIKYMHQTFFKQLIRAILKVSNASRTTKIVVIDDKKDADKDDDNDLDNGD  1350
1351  EVGRSKAKANDDDSSDDNDDDDATGVKLKQRKTDEKDYDDPDDVEELHDA  1400
1401  NDDDDEAEDEDDEEKGQDGNDNDGDDKAVERLLSNDMVKAYTYDKENHLW  1450
1451  CQVKLNLSVRYQKPDLTSIIRELAGKSVVHQVQHIKRAIIYKGNDDDQLL  1500
1501  KTDGINIGEMFQHNKILDLNRLYSNDIHAIARTYGIEAASQVIVKEVSNV  1550
1551  FKVYGITVDRRHLSLIADYMTFDGTFQPLSRKGMEHSSSPLQQMSFESSL  1600
1601  QFLKSAAGFGRADELSSPSSRLMVGLPVRNGTGAFELLTKIC          1642

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.)

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