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

NucPred

Fetching P30622 from www.uniprot.org...

The NucPred score for your sequence is 0.87 (see score help below)

   1  MSMLKPSGLKAPTKILKPGSTALKTPTAVVAPVEKTISSEKASSTPSSET    50
  51  QEEFVDDFRVGERVWVNGNKPGFIQFLGETQFAPGQWAGIVLDEPIGKND   100
 101  GSVAGVRYFQCEPLKGIFTRPSKLTRKVQAEDEANGLQTTPASRATSPLC   150
 151  TSTASMVSSSPSTPSNIPQKPSQPAAKEPSATPPISNLTKTASESISNLS   200
 201  EAGSIKKGERELKIGDRVLVGGTKAGVVRFLGETDFAKGEWCGVELDEPL   250
 251  GKNDGAVAGTRYFQCQPKYGLFAPVHKVTKIGFPSTTPAKAKANAVRRVM   300
 301  ATTSASLKRSPSASSLSSMSSVASSVSSRPSRTGLLTETSSRYARKISGT   350
 351  TALQEALKEKQQHIEQLLAERDLERAEVAKATSHVGEIEQELALARDGHD   400
 401  QHVLELEAKMDQLRTMVEAADREKVELLNQLEEEKRKVEDLQFRVEEESI   450
 451  TKGDLEQKSQISEDPENTQTKLEHARIKELEQSLLFEKTKADKLQRELED   500
 501  TRVATVSEKSRIMELEKDLALRVQEVAELRRRLESNKPAGDVDMSLSLLQ   550
 551  EISSLQEKLEVTRTDHQREITSLKEHFGAREETHQKEIKALYTATEKLSK   600
 601  ENESLKSKLEHANKENSDVIALWKSKLETAIASHQQAMEELKVSFSKGLG   650
 651  TETAEFAELKTQIEKMRLDYQHEIENLQNQQDSERAAHAKEMEALRAKLM   700
 701  KVIKEKENSLEAIRSKLDKAEDQHLVEMEDTLNKLQEAEIKVKELEVLQA   750
 751  KCNEQTKVIDNFTSQLKATEEKLLDLDALRKASSEGKSEMKKLRQQLEAA   800
 801  EKQIKHLEIEKNAESSKASSITRELQGRELKLTNLQENLSEVSQVKETLE   850
 851  KELQILKEKFAEASEEAVSVQRSMQETVNKLHQKEEQFNMLSSDLEKLRE   900
 901  NLADMEAKFREKDEREEQLIKAKEKLENDIAEIMKMSGDNSSQLTKMNDE   950
 951  LRLKERDVEELQLKLTKANENASFLQKSIEDMTVKAEQSQQEAAKKHEEE  1000
1001  KKELERKLSDLEKKMETSHNQCQELKARYERATSETKTKHEEILQNLQKT  1050
1051  LLDTEDKLKGAREENSGLLQELEELRKQADKAKAAQTAEDAMQIMEQMTK  1100
1101  EKTETLASLEDTKQTNAKLQNELDTLKENNLKNVEELNKSKELLTVENQK  1150
1151  MEEFRKEIETLKQAAAQKSQQLSALQEENVKLAEELGRSRDEVTSHQKLE  1200
1201  EERSVLNNQLLEMKKRESKFIKDADEEKASLQKSISITSALLTEKDAELE  1250
1251  KLRNEVTVLRGENASAKSLHSVVQTLESDKVKLELKVKNLELQLKENKRQ  1300
1301  LSSSSGNTDTQADEDERAQESQIDFLNSVIVDLQRKNQDLKMKVEMMSEA  1350
1351  ALNGNGDDLNNYDSDDQEKQSKKKPRLFCDICDCFDLHDTEDCPTQAQMS  1400
1401  EDPPHSTHHGSRGEERPYCEICEMFGHWATNCNDDETF              1438

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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