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

NucPred

Fetching Q19272 from www.uniprot.org...

The NucPred score for your sequence is 0.97 (see score help below)

   1  MSTRWRYYNSKRGNGFRGRGRGRGRGTSLTAVALPRDDNFHKGAQDGAYF    50
  51  KDMPMDPEQFRDETVLSLSFAQGMLGAAYYEQSSQLLKIMNDISEDLEFR   100
 101  FLKRLIDDVKPTLIIANRSQDLEFIKFLTTRYDPQEKIYEDGTTEEGTSE   150
 151  DTVPTWDSSLAYSTDETTAEKEEKEEDEDDDDEGLPAKLNKLPNNFFRMS   200
 201  RAIERLKAMAGSHDSSMTEEDKYIIIKMRFDIEAVNMIRSFGALLLFLDE   250
 251  TRMGVTDDPLSVTSPIKSIKTFTLGNLVEIDFNTIQALDILPKETENKKT   300
 301  FGQGRSLYQLMDKCRSTVGKKCLRKWFRNPTTDRDDLVSRQKCVHYFKQD   350
 351  WNAEVTAKLSSILGRVKALNSVFQKFQSGTAQLIHWECFVSTVNALVEIL   400
 401  NIIRQTPISKEFPVESDLLREVSEIAVIAGSIINFAESKIQGRVTVMNGI   450
 451  DEELDEIRDTYENMPMVLTAIAKQEEARLGLPPYSNVACVYIPLVGFVLS   500
 501  VPRDYGVESQPDMTLLYSTHEDLRVRNATTSRLDDEFGDILMRLIDSQTA   550
 551  IILTLKTRVMKKKRSIIKLLSIASRIDVLISFGLIAAQNGWNCPALVDEP   600
 601  VIEAVELYHPISVLVVKKSFVPNQVSSGRDGIKASIITGPNACGKSVYMK   650
 651  SIGIMVFLSHIGSFVPARHAKIGIVDRIVTRMFTVDSVLDGMSTFAKDVE   700
 701  QVALALRKATGNSLVIIDEFGKGTMTEVGLSLLASVMTYWMNRGADRCPH   750
 751  IFLSSHFHALPNYIPLETNIATFLTFTVLREAGGKIKYLFRMTPGLVDCS   800
 801  FALSVAKEEGIPPPVIGRACRIYKALKAGTLLKEIKAEVSNDNEKQLVED   850
 851  MDVVLADEDGFMAAVESFVKRKKTSFCESSMRNVSEEIEKERSEASTPAS   900
 901  KSRSTITARSNSVLSSRSMASVDQLSVLDALLPKKKKKKVTGSSMESSMS   950
 951  PDPFQEEDEGTEGEEDQISAPVSRPTLPSVQKYASEEEKQQSINSRHSFS  1000
1001  TRTAIHIPTPIQMGEAGGVKRPRSTSTSSPGPSASKSVRTEVFKKTPNVK  1050
1051  ESQVLETPKQLSISSFLEPKFPSSEKDVISRVSERYLQSDPFKTPISDRR  1100
1101  SQQSSRHSTPKNRSMNQSLIQSARDTPHETIRSSNEVNPEFFNIFNFPDD  1150
1151  SILKSQDTYDPNVTPRSSSRRELRPDVSHSQNSQFGEVFSELGTQFSIFN  1200
1201  SQQSFPGNSMGTTNPDCSIFDDFFANSQDGEKKIDSTKTSMPIVNSDNFI  1250
1251  FKTPEPRSSEKQRSLLKNKGQASNSSISPSSLILGQLAFGDVDQTPRPRG  1300
1301  DNPIEFQYDVVDDDDPIFEEKNCSAPVFEFLKSNDDEEDDEFLKSFLETE  1350
1351  GSLHIDTSADETIDRSKRS                                 1369

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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