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

NucPred

Fetching Q06811 from www.uniprot.org...

The NucPred score for your sequence is 0.46 (see score help below)

   1  TMEHYLKTYLSWLTEEQKEKLKEMKEAGKTKAEIQHEVMHYYDQLHGEEK    50
  51  QQATEKLKVGCKMLLKGIIGEEKVVELRNMKEAGADIQELQQKVEKMLSE   100
 101  VTDEKQKEKVHEYGPACKKIFGATTLQHHRRRRHHFTLESSLDTHLKWLS   150
 151  QEQKDELLKMKKDGKTKKELEAKILHYYDELEGDAKKEATEHLKGGCGEI   200
 201  LKHVVGEEKAAELKNLKDSGASKEELKAKVEEALHAVTDEEKKQYIADFG   250
 251  PACKKIYGVHTSRRRRHHFTLESSLDTHLKWLSQEQKDELLKMKKDGKAK   300
 301  KELEAKILHYYDELEGDAKKEATEHLKGGCAEILKHVVGEEKAAELKNLK   350
 351  DSGASKEELKAKVEEALHAVTDEEKKQYIADFGPACKKIYGVHTSRRRRH   400
 401  HFTLESSLDTHLKWLSQEQKDELLKMKKDGKTKKDLQAKILHYYDELEGD   450
 451  AKKEATEHLKDGCREILKHVVGEEKEAELKKLKDSGASKEEVKAKVEEAL   500
 501  HAVTDEEKKQYIADFGPACKKIFGAAHTSRRRRHHFTLESSLDTHLKWLS   550
 551  QEQKDELLKMKKDGKAKKELEAKILHYYDELEGDAKKEATEHLKGGCREI   600
 601  LKHVVGEEKAAELKNLKDSGASKEELKAKVEEALHAVTDEEKKQYIADFG   650
 651  PACKKIYGVHTSRRRRHHFTLESSLDTHLKWLSQEQKDELLKMKKDGKAK   700
 701  KELEAKILHYYDELEGDAKKEATEHLKGGCREILKHVVGEEKAAELKNLK   750
 751  DSGASKEELKAKVEEALHAVTDEEKKQYIADFGPACKKIYGVHTSRRRRH   800
 801  HFTLESSLDTHLKWLSQEQKDELLKMKKDGKAKKELEAKILHYYDELEGD   850
 851  AKKEATEHLKGGCREILKHVVGEEKAAELKNLKDSGASKEELKAKVEEAL   900
 901  HAVTDEEKKQYIADFGPACKKIYGVHTSRRRRHHFTLESSLDTHLKWLSQ   950
 951  EQKDELLKMKKDGKAKKELEAKILHYYDELEGDAKKEATEHLKGGCREIL  1000
1001  KHVVGEEKAAELKNLKDSGASKEELKAKVEEALHAVTDEEKKQYIADFGP  1050
1051  ACKKIYGVHTSRRRRHHFTLESSLDTHLKWLSQEQKDELLKMKKDGKAKK  1100
1101  ELEAKILHYYDELEGDAKKEATEHLKGGCREILKHVVGEEKAAELKNLKD  1150
1151  SGASKEELKAKVEEALHAVTDEEKKQYIADFGPACKKIYGVHTSRRRRHH  1200
1201  FTLESSLDTHLKWLSQEQKDELLKMKKDGKAKKELEAKILHYYDELEGDA  1250
1251  KKEATEHLKGGCREILKHVVGEEKAAELKNLKDSGASKEELKAKVEEALH  1300
1301  AVTDEEKKQYIADFGPACKKIYGVHTSRRRRYHAEDGTDDIDGLAQSRQR  1350
1351  RSGFFEKLIDVFAFF                                     1365

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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