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

NucPred

Fetching Q9BY12 from www.uniprot.org...

The NucPred score for your sequence is 0.97 (see score help below)

   1  MMASFQRSNSHDKVRRIVAEEGRTARNLIAWSVPLESKDDDGKPKCQTGG    50
  51  KSKRTIQGTHKTTKQSTAVDCKITSSTTGDKHFDKSPTKTRHPRKIDLRA   100
 101  RYWAFLFDNLRRAVDEIYVTCESDQSVVECKEVLMMLDNYVRDFKALIDW   150
 151  IQLQEKLEKTDAQSRPTSLAWEVKKMSPGRHVIPSPSTDRINVTSNARRS   200
 201  LNFGGSTGTVPAPRLAPTGVSWADKVKAHHTGSTASSEITPAQSCPPMTV   250
 251  QKASRKNERKDAEGWETVQRGRPIRSRSTAVMPKVSLATEATRSKDDSDK   300
 301  ENVCLLPDESIQKGQFVGDGTSNTIESHPKDSLHSCDHPLAEKTQFTVST   350
 351  LDDVKNSGSIRDNYVRTSEISAVHIDTECVSVMLQAGTPPLQVNEEKFPA   400
 401  EKARIENEMDPSDISNSMAEVLAKKEELADRLEKANEEAIASAIAEEEQL   450
 451  TREIEAEENNDINIETDNDSDFSASMGSGSVSFCGMSMDWNDVLADYEAR   500
 501  ESWRQNTSWGDIVEEEPARPPGHGIHMHEKLSSPSRKRTIAESKKKHEEK   550
 551  QMKAQQLREKLREEKTLKLQKLLEREKDVRKWKEELLDQRRRMMEEKLLH   600
 601  AEFKREVQLQAIVKKAQEEEAKVNEIAFINTLEAQNKRHDVLSKLKEYEQ   650
 651  RLNELQEERQRRQEEKQARDEAVQERKRALEAERQARVEELLMKRKEQEA   700
 701  RIEQQRQEKEKAREDAARERARDREERLAALTAAQQEAMEELQKKIQLKH   750
 751  DESIRRHMEQIEQRKEKAAELSSGRHANTDYAPKLTPYERKKQCSLCNVL   800
 801  ISSEVYLFSHVKGRKHQQAVRENTSIQGRELSDEEVEHLSLKKYIIDIVV   850
 851  ESTAPAEALKDGEERQKNKKKAKKIKARMNFRAKEYESLMETKNSGSDSP   900
 901  YKAKLQRLAKDLLKQVQVQDSGSWANNKVSALDRTLGEITRILEKENVAD   950
 951  QIAFQAAGGLTALEHILQAVVPATNVNTVLRIPPKSLCNAINVYNLTCNN  1000
1001  CSENCSDVLFSNKITFLMDLLIHQLTVYVPDENNTILGRNTNKQVFEGLT  1050
1051  TGLLKVSAVVLGCLIANRPDGNCQPATPKIPTQEMKNKPSQGDPFNNRVQ  1100
1101  DLISYVVNMGLIDKLCACFLSVQGPVDENPKMAIFLQHAAGLLHAMCTLC  1150
1151  FAVTGRSYSIFDNNRQDPTGLTAALQATDLAGVLHMLYCVLFHGTILDPS  1200
1201  TASPKENYTQNTIQVAIQSLRFFNSFAALHLPAFQSIVGAEGLSLAFRHM  1250
1251  ASSLLGHCSQVSCESLLHEVIVCVGYFTVNHPDNQVIVQSGRHPTVLQKL  1300
1301  CQLPFQYFSDPRLIKVLFPSLIAACYNNHQNKIILEQEMSCVLLATFIQD  1350
1351  LAQTPGQAENQPYQPKGKCLGSQDYLELANRFPQQAWEEARQFFLKKEKK  1400

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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