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

NucPred

Fetching Q90631 from www.uniprot.org...

The NucPred score for your sequence is 0.85 (see score help below)

   1  MEFYESTYFIILIPSVVITVIFLFFWLFMKETLYDEVLAKQKRDLKFPPT    50
  51  KSDKKKTEKKKNKKKEAQNGNIHESDSESTPRDFKLSDALGTDEEQVAPV   100
 101  PLSATEASAGIRERKKKEKKQKAAQDDHVTKESEGSKSSGKKVEPVPVTK   150
 151  QPTPPSEPAAAKKKPGQKKQKNDDQDTKTDSVASPAKKQEPVLLHQEVKQ   200
 201  ENVSGKKKVSAKKQKVLVDEPLIQPTTYIPLVDNSDAGALEKREVVEVAK   250
 251  QNMNEGIQKSGGKKMKNETDKENAEVKFKDFVMAMKNMIFTEDEARCVVE   300
 301  VLKEKSGAIHDVLQKASKAESAAAIHQLQDKEKLLAAVKEEAAVAKEQCK   350
 351  QLTQELVAEKERNGLLTAKMRERINALEKEHGTFQSKIHVSYQESQQMKI   400
 401  KFQQRCEQMEAEISHLKQENTILRDAVSTSTNQMESKQAAELNKLRQDCA   450
 451  RLVNELGEKNSKLQQEELQKKNAEQAVAQLKVQQQEAERRWEEIQVYLRK   500
 501  RTAEHEAAQQDVQNKLVAKDNEIQSLHSKLTDMVVSKQQLEQRMLQLIES   550
 551  EQKRASKEDSMQLRVQELVEQNDALNAQLQKLHSQMAAQTSASVLAEELH   600
 601  KVIAEKDKQLKQMEDSLGNEHANLTSKEEELKVLQNMNLSLKSEIQKLQA   650
 651  LTNEQAAAAHELERMQKSIHIKDDKIRTLEEQLREELAQTVNTKEEFKIL   700
 701  KDQNKTLQAEVQKLQALLSEPVQPTFEANKDLLEEMERGMRERDDKIKTV   750
 751  EELLEAGLIQMANKEEELKVLRTENSSLRKELQSLQIQLSEQVSFQSLVD   800
 801  ELQKVIHEKDGKIKSVEELLQAEILKVANKEKTVQALTQKIEALKEEVGN   850
 851  SQLEMEKQVSITSQVKELQTLLKGKENQVKTMEALLEEKEKEIVQKGERL   900
 901  KGQQDTVAQLTSKVQELEQQNLQQLQQVPAASQVQDLESRLRGEEEQISK   950
 951  LKAVLEEKEREIASQVKQLQTMQSENESFKVQIQELKQENCKQASLAVQS  1000
1001  EELLQVVAGKEKEIASLQNELACQRNAFEQQRKKNNDLREKNWKAMEALA  1050
1051  STEKLLQDKVNKTAKEKQQHVEAAEVETRELLQKLFPNVSLPANVSHSEW  1100
1101  ICGFEKMAKEYLRGASGSEDIKVMEQKLKEAEELHILLQLECEKYKSVLA  1150
1151  ETEGILQRLQRSVEEEESKWKIKVEESQKELKQMRSSVASLEHEVERLKE  1200
1201  EIKEVETLKKEREHLESELEKAEIERSTYVSEVRELKDLLTELQKKLDDS  1250
1251  YSEAVRQNEELNLLKMKLSETLSKLKVDQNERQKVAGDLPKAQESLASLE  1300
1301  REIGKVVGDANVIENSDVRTESELTDKRLNVAVNLNQDVGHLKKLLVSVS  1350
1351  QMLSKGREHYQLVE                                      1364

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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