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

NucPred

Fetching Q01613 from www.uniprot.org...

The NucPred score for your sequence is 0.93 (see score help below)

   1  MSAFGNTIERWNIKSTGVIAGLGHSERISPVRSMTTLVDSAYSSFSGSSY    50
  51  VPEYQNSFQHDGCHYNDEQLSYMDSEYVRAIYNPSLLDKDGVYNDIVSEH   100
 101  GSSKVALSGRSSSSLCSDNTTSVHRTSPAKLDNYVTNLDSEKNIYGDPIN   150
 151  MKHKQNRPNHKAYGLQRNSPTGINSLQEKENQLYNPSNFMEIKDNYFGRS   200
 201  LDVLQADGDIMTQDSYTQNALYFPQNQPDQYRNTQYPGANRMSKEQFKVN   250
 251  DVQKSNEENTERDGPYLTKDGQFVQGQYASDVRTSFKNIRRSLKKSASGK   300
 301  IVAHDSQGSCWIMKPGKDTPSFNSEGTITDMDYDNREQWDIRKSRLSTRA   350
 351  SQSLYYESNEDVSGPPLKAMNSKNEVDQTLSFQKDATVKSIPLLSQQLQQ   400
 401  EKCKSHPLSDLNCEKITKASTPMLYHLAGGRHSAFIAPVHNTNPAQQEKL   450
 451  KLESKTLERMNNISVLQLSEPRPDNHKLPKNKSLTQLADLHDSVEGGNSG   500
 501  NLNSSAEESLMNDYIEKLKVAQKKVLRETSFKRKDLQMSLPCRFKLNPPK   550
 551  RPTIDHFRSYSSSSANEESAYLQTKNSADSSYKKDDTEKVAVTRIGGRKR   600
 601  ITKEQKKLCYSEPEKLDHLGIQKSNFAWKEEPTFANRREMSDSDISANRI   650
 651  KYLESKERTNSSSNLSKTELKQIQHNALVQYMERKTNQRPNSNPQVQMER   700
 701  TSLGLPNYNEWSIYSSETSSSDASQKYLRRRSAGASSSYDATVTWNDRFG   750
 751  KTSPLGRSAAEKTAGVQRKTFSDQRTLDGSQEHLEGSSPSLSQKTSKSTH   800
 801  NEQVSYVNMEFLPSSHSKNHMYNDRLTVPGDGTSAESGRMFVSKSRGKSM   850
 851  EEIGTTDIVKLAELSHSSDQLYHIKGPVISSRLENTRTTAASHQDRLLAS   900
 901  TQIETGNLPRQTHQESVVGPCRSDLANLGQEAHSWPLRASDVSPGTDNPC   950
 951  SSSPSAEVQPGAPEPLHCLQTEDEVFTPASTARNEEPNSTAFSYLLSTGK  1000
1001  PVSQGEATALSFTFLPEQDRLEHPIVSETTPSSESDENVSDAAAEKETTT  1050
1051  TQLPETSNVNKPLGFTVDNQEVEGDGEPMQPEFIDSSKQLELSSLPSSQV  1100
1101  NIMQTAEPYLGDKNIGNEQKTEDLEQKSKNPEEDDLPKVKLKSPEDEILE  1150
1151  ELVKEIVAKDKSLLNCLQPVSVRESAMDLMKSLFPMDVTAAEKSRTRGLL  1200
1201  GKDKGETLKKNNSDLESSSKLPSKITGMLQKRPDGESLDDITLKKMELLS  1250
1251  KIGSKLEDLCEQREFLLSDISKNTTNGNNMQTMVKELCKPNEFERYMMFI  1300
1301  GDLEKVVSLLFSLSTRLTRVENSLSKVDENTDAEEMQSLKERHNLLSSQR  1350
1351  EDAKDLKANLDRREQVVTGILVKYLNEEQLQDYKHFVRLKTSLLIEQKNL  1400
1401  EEKIKVYEEQFESIHNSLPP                                1420

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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