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

NucPred

Fetching P12387 from www.uniprot.org...

The NucPred score for your sequence is 0.47 (see score help below)

   1  MGPAAGPSLLLLLLASVSLALGDPMYSIITPNILRLENEETVVLEAHEVQ    50
  51  GDIPVTVTVHDFPAKKNVLSSEKTVLTSATGYLGTVTIKIPASKEFKSDK   100
 101  GRKLVVVQAAFGGTQLEKVVLVSLQSGYLFIQTDKTIYTPGSTVLYRIFT   150
 151  VDSDLLPVGRTIIVTIETPDGIPIKRDTLSSNNQHGILPLSWNIPELVNM   200
 201  GQWKIQAFYENSPKQVFSAEFEVKEYVLPSFEVLVEPTEKFYYIDDPKGL   250
 251  EVNIIARFLYGKNVDGTAFVIFGVQDGDQRISLAQSLTRVVIEDGSGEVV   300
 301  LSRQVLLDGVQPSRPEALVGKSLYVSVTVILHSGSDMVEAERSGIPIVTS   350
 351  PYQIHFTKTPKYFKPAMPFEIMVLVTNPDGSPAPHVPVVTQGSNVQSLTQ   400
 401  ADGVARLSINTPNTRQPLSVTVQTKKGGIPDARQAINTMQALPYTTMYNS   450
 451  NNYLHLSMPRTELKPGETINVNFHLRSDPNQEAKIRYYTYLIMNKGKLLK   500
 501  VGRQPREPGQALVVLPMPITKELIPSFRLVAYYTLIGASAQREVVADSVW   550
 551  ADVRDSCVGTLVVKGGSGKDGQDKRQQHLPRQQMTLRIEGNQGARVGLVA   600
 601  VDKGVFVLNKKHKLTQSKIWDVVEKADIGCTPGSGKDYAGVFTDAGLSFK   650
 651  SSKAGLQTAQREGLDCPKPAARRRRSVQLMERRMDKAGKYKSKELRRCCE   700
 701  DGMRENPMQFSCQRRARYVSLGEACVKAFLDCCTYMAQLRQQHRREQNLG   750
 751  LARSDMDEDIIPEEDIISRSQFPESWLWTIEELKEPERNGISTKTMNIFL   800
 801  KDSITTWEILAVSLSDKKGICVADPFEVTVMQDFFIDLRLPYSVVRNEQV   850
 851  EIRAVLYNYREAQSLKVRVELLHNPAFCSLATAKKRHTQTVTIGPKSSVA   900
 901  VPYVLVPLKIGLQEVEVKAAVYNYFISDGVKKTLKVVPEGMRVNKTVAIR   950
 951  TLNPEQLGQGGVQREEIPAADLSDQVPDTDSETKILLQGTPVAQMAEDAV  1000
1001  DAERLKHLIITPSGCGEQNMIGMTPTVIAVHYLDQTEQWEKFGLEKRQEA  1050
1051  LNLINRGYTQQLAFKQPNWAYAAFKNRASSTWLTAYVVKVFSLAANLIGI  1100
1101  DSEVLCGAVKWLILEKQKPDGVFQEDGPVIHQEMIGGVRTAQEADVSLTA  1150
1151  FVLIALQEAKDICRAQVNNLEANINKAGDYIESRYADVRRPYTLAIAGYA  1200
1201  LALLERLNGATLQKFLNAATEKNRWEEARQKLYSVEATSYALLALLLLKD  1250
1251  FDAVPPVVRWLNEQRYYGRGYGSTQATFMVFQALAQYQTDVPDHKDLNME  1300
1301  VALQLPSRSSPSKFRLVWEAGSLLRSEATKQNEGFKLTAKGKGQGTLSVV  1350
1351  AVYYAKTKRKVVCKNFDLRVTLKPAPDTVKKPQEAKSTMILGICTRYLGD  1400
1401  QDATMSILDISMMTGFIPDTDDLKLLATGVDRYISKYEMNKDFSKNTLII  1450
1451  YLDKVSHSEEECLSFKIHQFFNVGLIQPGSVKVYSYYNLDETCTQFYHPE  1500
1501  KEDGMLNKLCHKDLCRCAEENCFIQLPEKITLDERLEKACEPGVDYVYKT  1550
1551  KLLKMELSDDFDEYIMTIEQVIKSGSDEVQAGKERRFISHIKCRDALHLK  1600
1601  EGKHYLMWGLSSDLWGERPNMSYIIGKDTWVEAWPEAEECQDEENQQQCQ  1650
1651  DLGTFTENMVVFGCPN                                    1666

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.