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

NucPred

Fetching P53254 from www.uniprot.org...

The NucPred score for your sequence is 0.70 (see score help below)

   1  MATSVKRKASETSDQNIVKVQKKHSTQDSTTDNGSKENDHSSQAINERTV    50
  51  PEQENDESDTSPESNEVATNTAATRHNGKVTATESYDIHIARETAELFKS   100
 101  NIFKLQIDELLEQVKLKQKHVLKVEKFLHKLYDILQEIPDWEEKSLAEVD   150
 151  SFFKNKIVSVPFVDPKPIPQNTNYKFNYKKPDISLIGSFALKAGIYQPNG   200
 201  SSIDTLLTMPKELFEKKDFLNFRCLHKRSVYLAYLTHHLLILLKKDKLDS   250
 251  FLQLEYSYFDNDPLLPILRISCSKPTGDSLSDYNFYKTRFSINLLIGFPY   300
 301  KVFEPKKLLPNRNCIRIAQESKEQSLPATPLYNFSVLSSSTHENYLKYLY   350
 351  KTKKQTESFVEATVLGRLWLQQRGFSSNMSHSGSLGGFGTFEFTILMAAL   400
 401  LNGGGINSNKILLHGFSSYQLFKGVIKYLATMDLCHDGHLQFHSNPENSS   450
 451  SSPASKYIDEGFQTPTLFDKSTKVNILTKMTVSSYQILKEYAGETLRMLN   500
 501  NVVQDQFSNIFLTNISRFDNLKYDLCYDVQLPLGKYNNLETSLAATFGSM   550
 551  ERVKFITLENFLAHKITNVARYALGDRIKYIQIEMVGQKSDFPITKRKVY   600
 601  SNTGGNHFNFDFVRVKLIVNPSECDKLVTKGPAHSETMSTEAAVFKNFWG   650
 651  IKSSLRRFKDGSITHCCVWSTSSSEPIISSIVNFALQKHVSKKAQISNET   700
 701  IKKFHNFLPLPNLPSSAKTSVLNLSSFFNLKKSFDDLYKIIFQMKLPLSV   750
 751  KSILPVGSAFRYTSLCQPVPFAYSDPDFFQDVILEFETSPKWPDEITSLE   800
 801  KAKTAFLLKIQEELSANSSTYRSFFSRDESIPYNLEIVTLNILTPEGYGF   850
 851  KFRVLTERDEILYLRAIANARNELKPELEATFLKFTAKYLASVRHTRTLE   900
 901  NISHSYQFYSPVVRLFKRWLDTHLLLGHITDELAELIAIKPFVDPAPYFI   950
 951  PGSLENGFLKVLKFISQWNWKDDPLILDLVKPEDDIRDTFETSIGAGSEL  1000
1001  DSKTMKKLSERLTLAQYKGIQMNFTNLRNSDPNGTHLQFFVASKNDPSGI  1050
1051  LYSSGIPLPIATRLTALAKVAVNLLQTHGLNQQTINLLFTPGLKDYDFVV  1100
1101  DLRTPIGLKSSCGILSATEFKNITNDQAPSNFPENLNDLSEKMDPTYQLV  1150
1151  KYLNLKYKNSLILSSRKYIGVNGGEKGDKNVITGLIKPLFKGAHKFRVNL  1200
1201  DCNVKPVDDENVILNKEAIFHEIAAFGNDMVINFETD               1237

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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