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

NucPred

Fetching P43638 from www.uniprot.org...

The NucPred score for your sequence is 0.79 (see score help below)

   1  MDSKDTQKLLKEHRIPCIDVGWLVRPSASTSKSSRPGKSESKANSVAPDI    50
  51  QMDTARPPVFETSVDSSSSILSSNDKGRRHSVAASLLMDNQRANAGSTSV   100
 101  PTNIPPPRGRSKSVVETNLSNVEADSGHHHHHRHHHHTEDAPAPKKVGFF   150
 151  KSLFGHRKKDQEQQEKERERKERSPSPTHVDRGAAIRRERTATISAESPP   200
 201  PLQYNAPPSYNDTVVPLTRSKTESEVYYENHPQSYYHGRMRTYHSPEEGK   250
 251  VDGTSPADDHNYGGSRPDPRLMDFLRYYKSKDYKLAAFKEGNFIKSSASP   300
 301  TTKKNRRASFSLHNDKPQPAKSLAHQKFDAKGRPIPPHPDAPKLPSAFRK   350
 351  KHPSNASIVDTVDSNSDVSSSAQNNNQTPSSHKFGAFLRKVTSYGNNNNN   400
 401  STNASSLSANVNNPDTSSTSLWSSSSMEFDPSKITTVPGLENIRPLKHVS   450
 451  FATNTYFNDPPQQICSKNPRKGEVEVKPNGSVVIHRLTPQERKKIMESTS   500
 501  LGVVVGGTGQLKLLNPEEDDANAKSKEEMAPQKQNEVEAHDEEDNNSQRR   550
 551  NIVMAAAEAAAEARAKEAPNELKRIVTNNEEEVTVSKTASHLTIDKPMIS   600
 601  RRGASTSSLASMVSSDTNGTNADDEGEILPPPSLKIPHDIVYTRCCHLRE   650
 651  ILPIPATLKQLKKGSTDPIPILQLRNPRPSMVEIWSFSDFLSIAPVLCLS   700
 701  LDGVQLTVQMLRIILSSLVYKQHFQKLSLRNTPLDEEGWKVLCYFVSKAK   750
 751  SLHSIDLTMVPSIKTNVQKPSKSSLKSKILRMQCNLENRSDMNWDLLTAS   800
 801  IALMGGLEEIVISGAKMNSAQFKNFILVACIATERLGLAYNGLSKSQCDD   850
 851  LAKWMVQSKVTGLDVGFNDLNGKLSSFTDAVLGKIQKANEKNVFKFLSLN   900
 901  GTNLRVNEHDTFENNEVLKLISVLCYLENLKFLDISNNPAIFPHCVPTLI   950
 951  DFLPVFVNLVRLHIDYNNLSSTSVVMLAEILPMCSRLNYFSMLGTELDLA  1000
1001  SSKALAEAVRKSSSLMTLDVDYVYMPENIKEKISLYALRNIQGELKRVNS  1050
1051  DDKDIKDSQFSSLQDQLSLLLTEKADNSEHYNKMVENFMAKIALARIKIS  1100
1101  KVVHDLFDLKLNGQLNLEGKEALIRLCFIEASLERGCDLLKQRHNNTLKS  1150
1151  PEAVSKSRKGGNQAQPNSESCQRMLLSSSILQNSDHIALMPFGSAIVEKS  1200
1201  SPDAEDAVEFREGDDSNVNHEDVPANDQQFRDEVDIKNKYSIIKRELEHE  1250
1251  KLVGGGDLPVDKEILNRAAQSLDSDQIKEFLLKNDVSTILGVIDELHSQG  1300
1301  YHLHHIFKKQGNQEETAFRTKDEQQSSQSNDSSANASPTTDPISTGSNTS  1350
1351  RTNDNAHIPPTDAPGFDKFMNNAEENAIDAAYDDVLDKIQDARNSSTK    1398

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.