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

NucPred

Fetching Q91ZT1 from www.uniprot.org...

The NucPred score for your sequence is 0.70 (see score help below)

   1  MQPGAALNRRLWLCLGLLQGLANGYSMTPPTLNITEDSYVIDTGDSLSIS    50
  51  CRGQHPLEWTWRGAQEVLTTGGKDSEDTQVVQDCEGTEARPYCKVLSLAQ   100
 101  THANNTGSYYCYYKYIKARIEGTTAASTYVFVRDFEQPFINKPDTLLVNR   150
 151  KDSMWVPCLVSIPGLNITLRSQSSVLHPDGQEVLWDDRRGMRVPTLLLRD   200
 201  ALYLQCETTWGDQDFLSNPFLVHITGNELYDIQLYPKKSLELLVGEKLVL   250
 251  NCTVWAEFDSGVTFDWDYPGKQAERAKWVPERRSQQTHTELSSILTIHNV   300
 301  SQHDLGPYVCEANNGIQQFRESTEVIVHEKPFISVEWLKGPVLEATAGDE   350
 351  MVKLPVKLAAYPPPEFQWYKDRKAVTGRHNPHALVLKEVTEASAGVYTLA   400
 401  LWNSAAGLRQNISLELVVNVPPHIHEKEASSPSIYSRHSRQTLTCTTYGV   450
 451  PQPLSVQWHWRPWTPCKTFAQRSLRRRQPRDGMPQCRDWKEVTTQDAVNP   500
 501  IESLDTWTESVEGKNKTVSKLVIQDANVSAMYKCVVFNKVGQDERLIYFY   550
 551  VTTIPDGFSIESEPSEDPLEGQSVRLSCRADNYTYEHLRWYRLNLSTLHD   600
 601  AQGNPLLLDCKNVHLFATPLEANLEEAEPGARHATLSLNIPRVAPEDEGD   650
 651  YVCEVQDRRSQDKHCHKKYLSVQALEAPRLTQNLTDLLVNVRTSLEMRCP   700
 701  VAGAHVPSIVWYKDERLLEKESGIDLADSNQRLSIQRVREEDAGRYLCSV   750
 751  CNAKGCVNSSASVAVEGSEDKGSMEIVILIGTGVIAVFFWVLLLLIFCNM   800
 801  KRPAHADIKTGYLSIIMDPGEVPLEEQCEYLSYDVSQWEFPRERLHLGRV   850
 851  LGHGAFGKVVEASAFGINKGSSCDTVAVKMLKEGATASEHRALMSELKIL   900
 901  IHIGNHLNVVNLLGACTKPNGPLMVIVEFCKYGNLSNFLRVKRETFDPYA   950
 951  EKSPEQRRRFRAMVEGAKADRRRLGSTDRALFTRFLMGKGSARRAPFVQE  1000
1001  AEDLWLSPLTMEDLVCYSFQVARGMEFLASRKCIHRDLAARNILLSESDI  1050
1051  VKICDFGLARDIYKDPDYVRKGSARLPLKWMAPESIFDKVYTTQSDVWSF  1100
1101  GVLLWEIFSLGASPYPGVQINEEFCQRLKDGTRMRAPELATPAIRHIMQS  1150
1151  CWSGDPKARPAFSDLVEILGDLLQGGGWQEEEEECMALHSSQSSEEDGFM  1200
1201  QASTTALHITEADAESSPPSMHCHSLAARYYNCVSFPGRLVRGTKAPGSS  1250
1251  RMKTFEELPMTPTTYKASVDNQTDSGMVLASEEFEQIESRHRQEGSFSRK  1300
1301  DPGQHMDISRGHPDLQGRRRRPTQGAQGGKVFYNNEYGEVSQPCTEGDCC  1350
1351  PSAGSTFFADSNY                                       1363

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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