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

NucPred

Fetching Q922B9 from www.uniprot.org...

The NucPred score for your sequence is 0.95 (see score help below)

   1  MNRPLSAEAEEELEWQVASRRRKAWAKCRSSWQASETEDLSTETTTQDED    50
  51  EDDEEDLPGTKLPAPAGRGNVPNEKIAIWLKDCRTPLGASLDEQSSGTPK   100
 101  GVLVRNGGSFEDDLSLGAEANHLHEPDAQVENCNNILAKERRLQFHQKGR   150
 151  SMNSTGSGKSSGTVSSVSELLELYEEDPEEILYNLGFGRDEPDIASKIPS   200
 201  RFFNSSSFARGIDIKVFLSAQMQRMEVENPNYALTSRFRQIEVLTTVANA   250
 251  FSSLYSQVSGTPLQRIGSMSSVTSTKEVADSPPPLTRSNTANRLMKTLSK   300
 301  LNLCVDKTEKGEGGSSPATEKGRTLSISLSEDGGGGKSDPKLQKVVKKKE   350
 351  SSSMLATVTEEVSGSSSTVTDSVDADRLSEEADSTISHQEESEESREAHS   400
 401  QEKDPLRKSAVTDPDLGHDGRVSSHCELESSSELKSAQASSSEKEPCAPL   450
 451  TIPSIRNIMTQQKDSFEMEEVQSTEGEAPHVPATCQLSLAKSKRDHLLRT   500
 501  ASQHSDSSGFAEDSTDCVSLNHLLVNESLQAMGSSADSCDSETTVTSLGE   550
 551  DHVTPTAQDQPYFNESEEESLAPLQKGRAKVEIVAEKRKADNQDFPQCVT   600
 601  AENAGNNESTKGPCEPGHQITETGEHPPLAATGELPREESVESDVEKGSE   650
 651  CEFAQYTTHHILRSLASFEAQGSGMSSEKKTGFPSSVDRVNTALQRAQMK   700
 701  VCSMSGQRVGRSLIKSKDLLKQRYLLAKAGYPLRRSQSLPTTLLSPVRVV   750
 751  SSVNVRLSPGKETRCSPPSFTYKYTPEEEQDLEKQGTEHDGQSLVKSTIF   800
 801  IPPPSVKKEEAPQSEGTRLEECHHGRLAPCPQFAPISQSTCSLHSVHSEW   850
 851  QDRPLCEHMRTLSAHSVPNISGAACSAFSPFGCPYSHRHAAHPYRACSVN   900
 901  PPSAIEMQLRRVLHDIRSSLQNLSQYPMTRGPDLAAAPYSTQNSSVLPLY   950
 951  ENTFQELQVVRRSLNLFRTQMMDLELAMLRQQTVVYPHMTEEDRYEVDQL  1000
1001  QGLRNSVRMELQDLEMQLEERLLGLDEQLRAVRVPSPFRPSALPGMCGSR  1050
1051  SVDNLSCPSPLNVMEPVTELIREQSYLKSELGLGLGDMAYEIPPGESSES  1100
1101  VFSQATSESSSVCSSPSHTNRRSRGLPGSKPRARLVARKKIFRASVALTP  1150
1151  TAPSRTGSVQTPPDLESSEEAGGAEEASPVVGLASHVEEEPEDLSLMPAA  1200
1201  EEMHRNVEQDELQQVIREIKESIVGEIRREIVSGLLAAVSSSKAPGPKQD  1250
1251  SH                                                  1252

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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