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

NucPred

Fetching Q922J3 from www.uniprot.org...

The NucPred score for your sequence is 0.89 (see score help below)

   1  MSMLKPSGLKAPTKILKPGSTALKTPAAAAAPVEKTIPSEKASGPPSSET    50
  51  QEEFVDDFRVGERVWVNGNKPGFIQFLGETQFAPGQWAGIVLDEPIGKND   100
 101  GSVAGVRYFQCEPLKGIFTRPSKLTRKVQAEDEANGLQAAPGRTASPLST   150
 151  AAATMVSSSPATPSNIPHKPSQSTAKEPSATPQISNLTKTASESISNLSE   200
 201  AGSVKKGERELKVGDRVLVGGTKAGVVRFLGETDFAKGEWCGVELDEPLG   250
 251  KNDGAVAGTRYFQCQPKYGLFAPVHKVTKIGFPSTTPAKAKAAAVRRVMA   300
 301  ATPASLKRSPSASSLSSMSSVASSVSSKPSRTGLLTETSSRYARKISGTT   350
 351  ALQEALKEKQQHIEQLLAERDLERAEVAKATSHVGEIEQELALARDGHDQ   400
 401  HVLELEAKMDQLRTMVEAADREKVELLNQLEEEKRKVEDLQFRVEEESIT   450
 451  KGDLEVATVSEKSRIMELEKDLALRAQEVAELRRRLESSKPPGDVDMSLS   500
 501  LLQEISALQEKLEAIHTDHQGEMTSLKEHFGAREEAFQKEIKALHTATEK   550
 551  LSKENESLRSKLDHANKENSDVIALWKSKLETAIASHQQAMEELKVSFSK   600
 601  GIGTDSAEFAELKTQIERLRLDYQHEIESLQSKQDSERSAHAKEMETMQA   650
 651  KLMKIIKEKEDSLEAVKARLDSAEDQHLVEMEDTLNKLQEAEIKVKELEV   700
 701  LQAKYTEQSEVIGNFTSQLSAVKEKLLDLDALRKANSEGKLELETLRQQL   750
 751  EGAEKQIKNLETERNAESSKANSITKELQEKELVLTGLQDSLNQVNQVKE   800
 801  TLEKELQTLKEKFASTSEEAVSAQTRMQDTVNKLHQKEEQFNVLSSELEK   850
 851  LRENLTDMEAKFKEKDDREDQLVKAKEKLENDIAEIMKMSGDNSSQLTKM   900
 901  NDELRLKERSVEELQLKLTKANENASFLQKSIGEVTLKAEQSQQQAARKH   950
 951  EEEKKELEEKLLELEKKMETSYNQCQDLKAKYEKASSETKTKHEEILQNL  1000
1001  QKMLADTEDKLKAAQEANRDLMQDMEELKTQADKAKAAQTAEDAMQIMEQ  1050
1051  MTKEKTETLASLEDTKQTNARLQNELDTLKENNLKTVEELNKSKELLSVE  1100
1101  NQKMEEFKKEIETLKQAAAQKSQQLSALQEENVKLAEELGRTRDEVTSHQ  1150
1151  KLEEERSVLNNQLLEMKKRESEFRKDADEEKASLQKSISLTSALLTEKDA  1200
1201  ELEKLRNEVTVLRGENATAKSLHSVVQTLESDKVKLELKVKNLELQLKEN  1250
1251  KRQLSSSSGNTDAQAEEDERAQESQIDFLNSVIVDLQRKNQDLKMKVEMM  1300
1301  SEAALNGNGEDLNSYDSDDQEKQSKKKPRLFCDICDCFDLHDTEDCPTQA  1350
1351  QMSEDPPHSTHHGSRSEERPYCEICEMFGHWATNCNDDETF           1391

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.