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

NucPred

Fetching Q10475 from www.uniprot.org...

The NucPred score for your sequence is 0.94 (see score help below)

   1  MSSKPPSNTPKFSYARALASSQSNKSNSTKASENNTATAEKQAVKPSGVE    50
  51  PTNTSRANAQKKTESTGKITSEADTEKYNSSKSPVNKEGSVEKKSSEKSS   100
 101  TNNKPWRGDNTSKPSANSSAERTSSQHQKPETSSQIGKDNAAPVENVNEK   150
 151  STSQETAPPVSTVPIQFGSITRNAAIPSKPKVSGNMQNKSGVSSYSSKSQ   200
 201  SVNSSVTSNPPHTEEPVAAKPEASSTATKGPRPTTSASNTNTSPANGAPT   250
 251  NKPSTDINTTDPATQTTQVSASNSPALSGSSTPSNTSSRSNRQNHGNFSE   300
 301  KRHYDRYGNSHPSYNKYSHYQHGFNYNNSGNNRNESGHPRFRNSRRNYNN   350
 351  QGAYPTYMSNGRSANQSPRNNPQNVNNGSTPIQIPVSLQTPYGQVYGQPQ   400
 401  YIVDPNMVQYGPILQPGYVPQYYPVYHQTPYTQNFPNMSRSGSQVSDQVV   450
 451  ESPNSSTLSPRNGFAPIVKQQKKSSALKIVNPVTHTEVVVPQKNASSPNP   500
 501  SETNSRAETPTAAPPQISEEEASQRKDAIKLAIQQRIQEKAEAEAKRKAE   550
 551  EKARLEAEENAKREAEEQAKREAEEKAKREAEEKAKREAEEKAKREAEEN   600
 601  AKREAEEKAKREAEEKAKREAEEKAKREAEEKAKREAEEKAKREAEEKAK   650
 651  REAEEKAKREAEENAKREAEEKAKREAEENAKREAEEKVKRETEENAKRK   700
 701  AEEEGKREADKNPEIKSSAPLASSEANVDTSKQTNATEPEVVDKTKVEKL   750
 751  KASEGKSTSSLSSPSHSTSSKRDLLSGLESLSLKTNPKSEQCLESLLNSQ   800
 801  FITDFSALVYPSTIKPPSTEEALKAGKYEYDVPFLLQFQSVYTDKPMKGW   850
 851  DERMKETVASAFSDKSSRGMYSSSRQSSRSGSNTHSHAGPGFGGPSERKG   900
 901  ISRLGIDRGFSSSGAGFGSGSNYKSAPSRGVSHHGHGGMSGSHRGSQRGS   950
 951  RRGGGERDKPDPSSLTIPVDQVAPLQLSANRWQPKKLTEKPAETKGEDEE  1000
1001  ALLPPEVVQRKVKGSLNKMTLEKFDKISDQILEIAMQSRKENDGRTLKQV  1050
1051  IQLTFEKATDEPNFSNMYARFARKMMDSIDDSIRDEGVLDKNNQPVRGGL  1100
1101  LFRKYLLSRCQEDFERGWKANLPSGKAGEAEIMSDEYYVAAAIKRRGLGL  1150
1151  VRFIGELFKLSMLSEKIMHECIKRLLGNVTDPEEEEIESLCRLLMTVGVN  1200
1201  IDATEKGHAAMDVYVLRMETITKIPNLPSRIKFMLMDVMDSRKNGWAVKN  1250
1251  EVEKGPKTIAEIHEEAERKKALAESQRPSSGRMHGRDMNRGDSRMGGRGS  1300
1301  NPPFSSSDWSNNKDGYARLGQGIRGLKSGTQGSHGPTSLSSMLKGGSVSR  1350
1351  TPSRQNSALRREQSVRAPPSNVAVTSANSFELLEEHDHDNDGGQKDSNSK  1400
1401  TSS                                                 1403

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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