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

NucPred

Fetching P41110 from www.uniprot.org...

The NucPred score for your sequence is 0.95 (see score help below)

   1  MSGARTVSTPTPPQTGGGVEPQANGETPQVAVIVRSDDRSQGAIIGGRPG    50
  51  LPGPEHSPSESQPSSPSPTPSPPPILEPGSEPNLAVLSLPGDTMTSGMIQ   100
 101  MPVEEPAPISREAGEPYCLSPEPTPLAEPILEVEVTLSKPVPVSEFSSSP   150
 151  IQVLTPLASHKMEIHEPNGVVPSEDLEPEVESSPELAPPPPPACLSESPV   200
 201  PIAPTTQPEELLNGAPSPPAVDLSPVCEPEDQAKEDTASATPPAVPSATP   250
 251  ATAPPATSPAQEEEGEEEEEEEEGEAGAAESDKGGEDLHPTESTPVPGHL   300
 301  PQNVEAVAATQVAVSVPKRRRKIKELNKKEAVGDLLDAFKEVNPAVPEVE   350
 351  NQPPAGNNPTPESEGSSGPSRPEEADETWDAKEDKIHNAENIQPGEQKYE   400
 401  YKSDQWRPLNLEEKKRYDREFLLGFQFIFCQYAEAGGLPHISDVVLEKAN   450
 451  KTPLRPLDPSRLSGINCGPDFTPSFANLGRPALSSRGPPRGGPGGELPRG   500
 501  AAGLGPRRSLQPRPPKGARKLIASVIMTEDIKLNKAEKAWKPSSKRTAAD   550
 551  KDRGEEDADGSKTQDLFRRVRSILNKLTPQMFQQLMKQVTQLAIDTEGAS   600
 601  KGSLTSSLRRPFQNPTSQWPSQHVPLPHGAESATTEKPTVTVNFRKLLLN   650
 651  RCQKEFEKDKDDDEVFEKKQKEMDEAATAEERERLKEELEEARDIARRCS   700
 701  LGNIKFIGELFKLKMLTEAIMHDCVVKLLRHDEESLEFLCRLLTTIGKDL   750
 751  DFEKAKPRMDQYFNQMEKIIKEKKTSSRIRFMLQDVLDLRQSNWVPRRGD   800
 801  QGPKTIDQIHKEAEMEEHREHIKVQQLMAKGSDKRRGGPPGPPISRGLPL   850
 851  VDDGGWNTVPISKGSRPIDTSRLTKITKPGSIDSNNQLFAPGGRLSWGKG   900
 901  SSGSGAKPSDAASEVSRPATSTLNRFSALQQAVPTESTDNRRVVQRSSLS   950
 951  RERGGKAGEPRRRLERSERGGDRGDRLDRARTPATKRSFSKEVEERSRER  1000
1001  PSQPEGLRKAASLTEDRDRGRDAAKREAALPPVSCAKAALSEEELEKKSK  1050
1051  AIIEEYLHLNDMKEAVQCVQELASPSLLFIFVRHGIESTLERSAIARERM  1100
1101  GQLLHQLLCAGHLSTAQYYQGLYEILELAEDMEIDIPHVWLYLAELVTPI  1150
1151  MQEGGVPMGELFREITKHLRPLGKAASLLLEILRLLCKSKGPKKVAYCGV  1200
1201  RLGSAGKNFCLEGQDVGAFITEQKVEYTLGEESEAPGQRALSSEELSRQL  1250
1251  EKVLKEGSSNQRVFDWIEANLSEQQIASNTLVRALMTAVCYSAIIFETPL  1300
1301  RVDVAVLKGDRICYRNTCVIAEGAARLYALQALVVTLEQPANLLRMFFDA  1350
1351  LYDEDVVKEEAFYSWESSKDPAEQQGKGVALKSVTAFFKWLREVEEEESD  1400
1401  HN                                                  1402

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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