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

NucPred

Fetching P10511 from www.uniprot.org...

The NucPred score for your sequence is 0.89 (see score help below)

   1  MQNLAPWESFFMFVNILLRDYEPVKRRQQGSESNEVMKYSFTVDTLICRE    50
51 LFRSILKEKTLGILGDYLNRECIFERTKKLVKLNYNDDEYDYDLDDILKI 100
101 RKNSSGKLIVDDIDQAIFIIDHLSRKVDCKVFTKKSLVGFRHIEKTITEA 150
151 GYKIRERRSIGLDWYTLLNDIRTSCAKHRTFVAFSKYRYVDFIAMLTAFH 200
201 QVKAAKSNEEEHLSTIYSLYPFVEHNFDEDKEDAATTKQTTTTTTTTPQT 250
251 RTRKRQATGDNTPTPTPAPAPKPTTPKPTPAPRKISSRKNGGLTNVRVDH 300
301 ISVNNIPTPSDTNESLSPPSTIISSSNSIKQCLVEVLESKGEISIDKIKS 350
351 IFNCLQNKQYTGDLIDSMFQQNKSEKVITISSKLFNMSNKVDYDEINFAK 400
401 LKDDILYLSRRLIYEKNTNLLIPTEEGEGIIGFLWLPVVNGALTASVYVS 450
451 QLGADVDFKKISATVRFVQLCISMSDIIGFMELRSLSLDAFRSIANELLY 500
501 MSDRILNLEADLRTLKDIVMKPTNLKKHVNVDNLFSRLSPEGSNGFANYL 550
551 YDFISNHPYIKIDKSQNSIKLKETPNPVLVLTYDPKVVEHKVGFLFHCRS 600
601 EISRFNAGGNKFILNNIQHSFTPNNIGVLSQDRENDLKRNYSMLTSNTSK 650
651 LITGTGSGEHNLERFISITINNTAYDLIRVVLFRDISNGISISNLRDIFR 700
701 ENSDNRNRYLEYLGKSRLIRVFFIAPCLIQILEVNFAATQLTADKNFNRA 750
751 IKSIKIRNLSYITIDIIVGGNVIDSIRGDATQVVQINASEFSFSVSCLKF 800
801 SVSATLVSKKNLQNISTIVLNKYNEEKSYLQCVKKFSKLSKSFIRKFTGM 850
851 NININALEELLLSEAGAYEDDDDDEGEGNEDDEDNDENEDEDEGEGEGDS 900
901 SEDEDE 906

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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