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

NucPred

Fetching P39113 from www.uniprot.org...

The NucPred score for your sequence is 0.87 (see score help below)

   1  MANNNSDRQGLEPRVIRTLGSQALSGPSISNRTSSSEANPHFSKNVKEAM    50
  51  IKTASPTPLSTPIYRIAQACDRCRSKKTRCDGKRPQCSQCAAVGFECRIS   100
 101  DKLLRKAYPKGYTESLEERVRELEAENKRLLALCDIKEQQISLVSQSRPQ   150
 151  TSTDNTINGNFKHDLKDAPLNLSSTNIYLLNQTVNKQLQNGKMDGDNSGS   200
 201  AMSPLGAPPPPPHKDHLCDGVSCTNHLHVKPTSTSLNDPTAISFEQDEAP   250
 251  GLPAVKALKSMTTHQRSTQLATLVSLSIPRSTEEILFIPQLLTRIRQIFG   300
 301  FNSKQCLYTVSLLSSLKNRLPAPRLLAPSTSTKLKEKDEDKKLDDDSAFV   350
 351  KRFQSTNLSEFVDLKKFLISLKFNINSFSKQSEKPANDQDDELLSLTEIK   400
 401  ELLHLFFKFWSNQVPILNNDHFLIYFNNFVEVVKHLSTENLETNNTTKST   450
 451  VTTNHEIFALKLLMMLQMGLLVKIKMEKIKYTVPKNPKAKYARLMAYYHQ   500
 501  LSLIIPKNPYFLNMSTTSLPSLQLLSLASFYYLNVGDISAIYGVRGRIVS   550
 551  MAQQLRLHRCPSAVLSVHSNPVLQKFEQSERRLLFWAIYYVDVFASLQLG   600
 601  VPRLLKDFDIECALPISDVEYKDQLSMENEKADKKAKKIQLQGQVSSFSL   650
 651  QIIRFAKILGNILDSIFKRGMMDERITSEVALVHENALDNWRNQLPEMYY   700
 701  FQITVNGTVNLDEIRATNQRNTETKFDKKDIILFEKKILLLFYFLAKSMI   750
 751  HLPVIATKPLPKNVDNATKKKQSMFNNDSKGATNQDHMILDVDMTSPAIR   800
 801  TSSSYIILQQATNATLTIFQAINSMYLPLPLNVSRTLIRFSLLCARGSLE   850
 851  YTKGGALFLDNKNLLLDTIKDIENDRLLDLPGIASWHTLKLFDMSINLLL   900
 901  KAPNVKVERLDKFLEKKLNYYNRLMGLPPATTTSLKPLFGSQSKNSLENR   950
 951  QRTPNVKRENPEHEYLYGNDSNNNNNSEAGHSPMTNTTNGNKRLKYEKDA  1000
1001  KRNAKDGGISKGENAHNFQNDTKKNMSTSNLFPFSFSNTDLTALFTHPEG  1050
1051  PNCTNTNNGNVDVCNRASTDATDANIENLSFLNMAPFLQTGNSNIGQNTI  1100
1101  ENKPMHMDAIFSLPSNLDLMKDNMDSKPEQLEPVIKQNPENSKNNQFHQK  1150
1151  GKSTNMEKNNLSFNNKSNYSLTKLMRLLNNDNSFSNISINNFLYQNDQNS  1200
1201  ASADPGTNKKAVTNAGANFKPPSTGSNTSQGSILGSTKHGMDNCDFNDLG  1250
1251  NFNNFMTNVNYSGVDYDYIVDASLGLAPLLVDTPDISNTNTTSTTSNRSK  1300
1301  NSIILDTTFNDDLDRSRMNAREVLNPTDSILSQGMVSSVSTRNTSNQRSL  1350
1351  SSGNDSKGDSSSQENSKSATGNQLDTPSTLFQMRRTSSGPSASHRGPRRP  1400
1401  QKNRYNTDRSKSSGGGSSNTDNVSDLFQWQNAK                   1433

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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