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

NucPred

Fetching P01132 from www.uniprot.org...

The NucPred score for your sequence is 0.63 (see score help below)

   1  MPWGRRPTWLLLAFLLVFLKISILSVTAWQTGNCQPGPLERSERSGTCAG    50
  51  PAPFLVFSQGKSISRIDPDGTNHQQLVVDAGISADMDIHYKKERLYWVDV   100
 101  ERQVLLRVFLNGTGLEKVCNVERKVSGLAIDWIDDEVLWVDQQNGVITVT   150
 151  DMTGKNSRVLLSSLKHPSNIAVDPIERLMFWSSEVTGSLHRAHLKGVDVK   200
 201  TLLETGGISVLTLDVLDKRLFWVQDSGEGSHAYIHSCDYEGGSVRLIRHQ   250
 251  ARHSLSSMAFFGDRIFYSVLKSKAIWIANKHTGKDTVRINLHPSFVTPGK   300
 301  LMVVHPRAQPRTEDAAKDPDPELLKQRGRPCRFGLCERDPKSHSSACAEG   350
 351  YTLSRDRKYCEDVNECATQNHGCTLGCENTPGSYHCTCPTGFVLLPDGKQ   400
 401  CHELVSCPGNVSKCSHGCVLTSDGPRCICPAGSVLGRDGKTCTGCSSPDN   450
 451  GGCSQICLPLRPGSWECDCFPGYDLQSDRKSCAASGPQPLLLFANSQDIR   500
 501  HMHFDGTDYKVLLSRQMGMVFALDYDPVESKIYFAQTALKWIERANMDGS   550
 551  QRERLITEGVDTLEGLALDWIGRRIYWTDSGKSVVGGSDLSGKHHRIIIQ   600
 601  ERISRPRGIAVHPRARRLFWTDVGMSPRIESASLQGSDRVLIASSNLLEP   650
 651  SGITIDYLTDTLYWCDTKRSVIEMANLDGSKRRRLIQNDVGHPFSLAVFE   700
 701  DHLWVSDWAIPSVIRVNKRTGQNRVRLQGSMLKPSSLVVVHPLAKPGADP   750
 751  CLYRNGGCEHICQESLGTARCLCREGFVKAWDGKMCLPQDYPILSGENAD   800
 801  LSKEVTSLSNSTQAEVPDDDGTESSTLVAEIMVSGMNYEDDCGPGGCGSH   850
 851  ARCVSDGETAECQCLKGFARDGNLCSDIDECVLARSDCPSTSSRCINTEG   900
 901  GYVCRCSEGYEGDGISCFDIDECQRGAHNCGENAACTNTEGGYNCTCAGR   950
 951  PSSPGLSCPDSTAPSLLGEDGHHLDRNSYPGCPSSYDGYCLNGGVCMHIE  1000
1001  SLDSYTCNCVIGYSGDRCQTRDLRWWELRHAGYGQKHDIMVVAVCMVALV  1050
1051  LLLVLGMWGTYYYRTRKQLSNPPKNPCDEPSGSVSSSGPNSSSGAAVASC  1100
1101  PQPWFVVLEKHQDPKNGSLPADGTNGAVVDAGLSPSLQLGSVHLTSWRQK  1150
1151  PHIDGMGTGQSCWIPPSSDRGPQEIEGNSHLPSYRPVGPEKLHSLQSANG  1200
1201  SCHERAPDLPRQTEPVQ                                   1217

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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