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

NucPred

Fetching P35820 from www.uniprot.org...

The NucPred score for your sequence is 0.99 (see score help below)

   1  MMTPESKAIQPAAATTKQTAEATATTTMAHTQQKSQLSTLAKTTTTTATN    50
  51  KAAKSVVSNANSSGNNSSKKLALSQSQKTTTTTTPPTTTTTTTAAAAAEA   100
 101  TTNADKMQKQQQLKQQLFAACSIKVKSENTLATTANAALAAATTTTTTAT   150
 151  PALATGKAAKTILENGIKKESTPPAVESVEASSSSSSSSSSSSSSSSSWP   200
 201  TTRRATSEDASSNGGASADEEKSEEDPTAAVAASSTATTTSDLATTSRPR   250
 251  PVLLTAVNPHIICHLCQGYLINATTIVECLHSFCHSCLINHLRKERFCPR   300
 301  CEMVINNAKPNIKSDTTLQAIVYKLVPGLYERELMRKRAFYKDRPEEAAL   350
 351  ATPEQRGDDTEHLIFSPSDDMSLSLEYAELGELKTDSEPELVDTLRPRYL   400
 401  QCPAMCRVSHLKKFVYDKFEIDAQRFSIDIMYKVKTIVLLDYYTLMDIAY   450
 451  IYTWKRDAPMRFYYRVYESPQPLVKPAPRRVLPLKLEKQERENQEQQLAV   500
 501  EVASSKVEPVSLPEDQKAEASIKVEEQESTREIVKEVIKDVAATPPTETL   550
 551  KLVINRNMLDKREKSHSPQMSSKSSSKSSPCTPVSSPSEPNIKLKIDLSK   600
 601  QNSVTIIDMSDPERREIVKPLKPEKESRSKKKDKDGSPKSSSSSSSSSSG   650
 651  ERKRKSPSPLTVPPLTIRTERIMSPSGVSTLSPRVTSGAFSEDPKSEFLK   700
 701  SFALKPIKVKVESPERTLNNRAITPPSPSVQQSASPKSKGNNLDDSILMK   750
 751  PPSCMPPKSIASSKRKSKEPVKAVSKKQKLSPPLPTVDFKIRLPVTNGNS   800
 801  SGTASPKIEKPLMPPPAKPPMLAPRKLQPSAQFAPPPSPIHHHAGVQMSA   850
 851  PGNRTPIAKRYQPILPKASRPNPFANIPNDVNRLLKDAGTEIKSIGGGSV   900
 901  ENNSNAAQKPHLYGPKGESKMGPPALPATTPSQGNKNVGKQAGNLPMSAP   950
 951  PNKGNSSNNYLNLALFNSSKCKGKEAPPGCRTPMYTPNSPIYSPSSPQYV  1000
1001  PSYNIPTMPTYKYTPKPTPNSGSGNGGSGSYLQNMLGGGNGGSLGGLFPS  1050
1051  PPTKSDQNTNPAQGGGGSSSATQSGGNNGIVNNNIYMPNEDAPEKQQVKV  1100
1101  KSLLNSCNINIPSSLSITISRDNGDSSSPNNGQHPKHKSPVNNYIEIVKL  1150
1151  PDQPQDQVQAAKEAQKRQSPPAAVPGHLAAKLPPPPPSKAIPSPQHLVSR  1200
1201  MTPPQLPKVATPPPPSSPRVITPPKTSPPANAAKVTPLKPVLTPTQVDKK  1250
1251  TPSPEKRTAAQMGSHSPTASENKSPKGGPAGVANSTGGAQNGDPAAKKFR  1300
1301  PILPRQNGMPELAPKLPTLAPFVGFNPLQNPAAGKKVPPSKKSPNAGAAA  1350
1351  HQSGQQKLVNGGQSQPAQQKTSPPAQKNQQQVKKVSKNPTPPPPSLPAVG  1400
1401  KMMPHPVMHSQNAPLSIASSASAAAVASGQLDLSNFLKENLRRVHAAQAA  1450
1451  QAAQVAAAANQSNMMYNLAQMGHMTPAMYNYQQAYFREQLSRMQRVGNEV  1500
1501  FNDYLQKLKTAAATGGGGPVEGELKPMLPTVTLPSPGATPPAASPKTSPL  1550
1551  PAGKLTAAATAPQTKGNSSSGAANARQQTAATGNNGATVPAASLPPATKS  1600
1601  K                                                   1601

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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