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

NucPred

Fetching P47054 from www.uniprot.org...

The NucPred score for your sequence is 0.61 (see score help below)

   1  MKWSAIPFQTLYRSIESGEFDFDLFKEVLPDLQNLNLNTDKLKNNASRSQ    50
  51  LEKGEIELSDGSTFKVNQEFIFEAISLSDELNLDEIVACELILSGDTTAN   100
 101  NGKVQYFLRRQYILQIVSFIVNCFHEDTELYQELIKNGALVSNILSAFKF   150
 151  IHTQLSEIKQQINKAQILENYNALFQQNIKFRRDFLLREYDILSQILYGL   200
 201  VDKGAIMKNKDFILSLLHHVSELDSNDFFIIYYTPAFFHLFASLRVLPDA   250
 251  DVKLLHSQFMKDLKDDSIYTKPVKVALIFIFFAYFIGWCKEDPKRRADTM   300
 301  DFKTDVDEPMTSAVELGAIEQILIFAADTSIVEQDKSMELFYDIRSLLER   350
 351  HIPRLIPKQLLDDEKIFSQTTNSTYNPASATDNMSGRGLWNPSYPGMMST   400
 401  TGTARLNSMPNNVNEYSYTTIVLSDQTQEFFLSSFDDVLQTIITDCAFLL   450
 451  TKIKDAEEDSLLSGEDLTLDDISLKADLERFFLSIYFFYASRPEYSCTFW   500
 501  SDKESNAYGFIEWCSRCNDNLMRSCFYLMVSSLSFGPENALNVYHYFGEN   550
 551  SSISWKNIAQCLSDYTKKISNFNSSLHKRQQFSESTHNDIDSTAVALEEG   600
 601  LNEEAVIFLSSLLTLVGSVTYQVDEDVKSSLSKVFSDVLFEFTKINTPLV   650
 651  GAAFKVISNLVPKLESSRTKFWSFLDSLIFKDSSLNYSSESYRNAFTNVL   700
 701  TKYSDVLGFLQLFHNLISIHSRENNSEYMVFGKLAFPTRLGQGYRKVGIW   750
 751  PYFDYIFNDILAHVDQIVDIRNKRAVQLPILKIIYTGLCSFDYSVILNSI   800
 801  PAAANLDALVDCENFFNYVQECPAIPIFNYIFTEKIYKSIFNVVDVGVDQ   850
 851  LSIELEGGKNQAELLQLAVKIINKVLDYQETYVEELFPIVKKHGKTDYFL   900
 901  PKNYSLHGLRSFYDAIFFNIPLVAHLGLYVGVDDQILATNSLRILAKLSE   950
 951  RSNGSVASLSKRNKLLTIFDSVDESARIKDAFITQLESSITDAGVLALKL  1000
1001  ELLDFLTSNLSNYSRTMTISHLLLGFQVSNVISLGPNLATFISSGTSLLD  1050
1051  SLISVLEASLNSITKDNIDYAPMRLATAALEIILKLCRNPLTSGLLYSYL  1100
1101  IKENFFERIMILDPQVTRFTTWNGSPFDNSTEEKCKNFIESESVGAFLSF  1150
1151  LAYRNYWTQYLGLFIHKISFSGTKSEVLTYVNYLISNTMYSVRLFSFLDP  1200
1201  LNYGNICEPKETLSIFTNVPLNLEQVTLNKYCSGNIYDFHKMENLMRLIK  1250
1251  RVRAESLHSNSFSLTVSKEQFLKDADVECIKAKSHFTNIISRNKALELNL  1300
1301  SVLHSWVQLVQIIVTDGKLEPSTRSNFILEVFGTIIPKISDYIEFNITFS  1350
1351  EELVSLAVFLFDIYNRDRKLITDKGTVDGRLYQLFKTCIQGINSPLSSVA  1400
1401  LRSDFYILANHYLSRVLSDQVGSEKVLQDLRLGSKKLVEIIWNDVVYGEG  1450
1451  TSRVTGILLLDSLIQLANRSKENFILDSLMKTTRLLLIIRSLKNTDALLN  1500
1501  STTEHINIDDLLYELTAFKATVFFLIRVAETRGGASALIENNLFRIIAEL  1550
1551  SFLKVDPDLGLDLMFDEVYVQNSKFLKVNVTLDNPLLVDKDANGVSLFEL  1600
1601  IVPIFQLISAVLVSMGSSNKAVVQTVKGLLNTYKRLVIGIFKRDLLREKE  1650
1651  DKKNSSDPNNQSLNEMVKLIVMLCTLTGYQNND                   1683

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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