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

NucPred

Fetching O13394 from www.uniprot.org...

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

   1  MNPFESLPDAARPAQGTRPNRSDGPPPLPPLTIPGSTGRPQNPIFSPPPN    50
  51  LHHILPPGYLPQQQQQQQQQQQQQQQRSQQPFFSPPPPDAMSPPLGSHQA   100
 101  YLNSTSSQPTQRLPGISFQEPQRMPVQRSGPSRDSVKSYGDDKRSINDPN   150
 151  SSSTALTQVNSLDPESGFSAHNDTFRRKKSLVRPDRERMDPSHRQWYYRN   200
 201  HAAHMDVMAASGGRVGYMPSTTGHLPQHGAAPHGSGMAGIVGPGGGLSGL   250
 251  GVTGPTNVPPGGLGRAPPLRRGKSLLGRDEDQVETGINVLKRGVSLRRKQ   300
 301  SKSGNKPSKEVPRDLGESKTSRIAPGPVGGWMIYCYILTICCPGPFLRIF   350
 351  GIRTPEQQRAWREKMGLIGIITLIMAAVGFLTFGFTQTVCGQQPDRYTLG   400
 401  TIDVGSMTFNGYDYSFDGFIHPQVGPFGADTIYNRTNPIYSEPWSSGGQD   450
 451  GSLLFQKIGAACTGIISNRAGGAQPERYFDCTLVRQDGKGGYANSTMPMC   500
 501  HTGSIVDQFNDGAQPRNSVLKKRGQVSLQWNNVTDPARNLAVYRGSVLDL   550
 551  NRLNNLTTGLSYPELYDTLKRRNDSWAGRDVTSAVMRQRLEREFQCLEQI   600
 601  TRVGFIDSETIGCVASKVELYLSLVFIIGVVAIKFFMAVMFGWFISWRLG   650
 651  NYANETYEQRMKRAAEIEQWSDDIYRPAPAGYRPNARKHKSFLPAKSRFS   700
 701  VADPLSLKSGSRAPMPLSEKRMTRASRLGVASPLGGSPPGSPSVAGGRSS   750
 751  ASLAPAHSRRSSFSGSPAEGAMGVCPFPLHNTIPQPGPDYRPFGFQLAHS   800
 801  ICLVTAYSESFEGLRTTLDSLATTDYPNSHKLLLVIADGIVKGAGSDIST   850
 851  PDICLSMMKDLVIPAEEVEGNSYVAIADGYKRHNMCKIYAGFYDYDDETV   900
 901  ERSKQQRVPMILVAKCGTPLEADSAKPGNRGKRDSQVLLMAFMQKVMFDE   950
 951  RMTAFEYEFFNSIWRVTGVSPDNYEIVLCVDADTKVFPDSLSRMVACMVE  1000
1001  DPEIMGLCGETKIANKSETWVTMIQVFEYYISHHQTKAFEACFGGVTCLP  1050
1051  GCFSAYRIKAPKGPHGYWVPILANPDIVEHYSENVVDTLHKKNLLLLGED  1100
1101  RYLTTLMLKTFPKRKMMFVPQAVCKTIVPDTFRILLSQRRRWINSTVHNL  1150
1151  FELVMVNDLCGTFCFSMRFVVFMELTGTLVLPAAIAFTLYVVVQAFLPNV  1200
1201  PTPTIPLILLALILGLPGILIVVTSRKIAYVGWMLIYLLSLPIWNFVLPL  1250
1251  YAYWHMDDFSWGATRVVQGENKKDNHGDADGKFDPSHIVMKRWAEFERER  1300
1301  RWKSGTHSRDSTYDVVQRTGSPERAGSTRYSVVSSDTFHSSPFGQHDQFG  1350
1351  RALPNAMSSSSASQFGPDVSEVSHSKSPSGARARLDAVPLLELPAPLATD  1400
1401  AKHRSGASPTGTVVVPRPRATSPAPLPHNSGHPALGSVSAFSPTQHSAGR  1450
1451  LPTLPGAATYEAYPHTDAADEERRPMIGSTSSSPDPEPRRYIGPDAGVRH  1500
1501  GNVSTEQRYPTVSESAYPMQAYTAEPETDGSASPTPAQQGFNAANSNQQT  1550
1551  RPLTRGFSLVDDGPVASAQGVRQVQRGARRSQMPNSAASPPPANRTGNLP  1600
1601  PGAAPPSFD                                           1609

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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