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

NucPred

Fetching O13735 from www.uniprot.org...

The NucPred score for your sequence is 0.89 (see score help below)

   1  MFNNGDNMSRERFSSNHSMQRQKTESRANFSRRLVPSDSNRKPVPNGASN    50
  51  SPLSRDAASHLISTIETSIMKLLVVTKELLESLTNWSKGTVNDSAVSSVY   100
 101  VTLIGEFLQTTKSFHEAGIETADLNDFPLELRSVLEQTLEKTPSSDALET   150
 151  NLPNVRELVMHLLQSLKYKQSLVKSRLNQSRSNLPQMTREANDNDVNRRN   200
 201  SRGSSQGSISSFRNPDSRKQYEETTSASLSAPGAFDALKQTNALERRASK   250
 251  RLSHMVKDQQNNEGSSQNLRNITVESVRGFLRDSSKPDNIMDSPSPKVSK   300
 301  RPSIVRQDSHDSNKLSRRPTINTSFDRKFSPKLTRTPSLTKSLDPGTPTS   350
 351  LKSPSLRKSPSSFVQKDVYSRSNSLRISQANRSNVFPGATDVTRSVSDHR   400
 401  ILSSSTINDGEVAPPLPQRSRTISSPNSPLSATVLPSSTPILLPRGRSST   450
 451  LSVNKKQFNADDGSTLNSPNSIRETEEYAASPKLEDIADEVETDATSQRE   500
 501  LLERQIQKAESSEDTSEIESLQGKLSLPQVSSTQQEIQPSSSVPEAASNE   550
 551  IAEKEPAVTAIESITERKEEAPVISSSEKIESGTSISTSDTKGGLANFEN   600
 601  DSLEELERLIQQNNAEQDEPSYKFHKYEYSSEESGSEDEFKSEKDTKGYV   650
 651  ISNDDSTQVEEDSEDKSTPNTGASAKLINDPSSTITVSDVYPKKPASPVE   700
 701  ITEPPSSALVSATSPTTNVPIVPEAVHLSTAFSTAPVSTIVSNISPLPTV   750
 751  APPNVSGSPSETPISKPEKVPVVSQTEKALPKPLGVDTEKYYFLRYNNQT   800
 801  RKVKVESPLSNANELGELFSNVYKISFSGDSYELNIEDPDTKISYLLEDL   850
 851  SDLKYKSLVSFMFKEQDANKKREDFHSGEVSAIQHSSAQNTLDDHVNTTT   900
 901  HESPSSAFTEILERLKAIEQNISTNHTNDSAALKSSEDHSKLANNFSVPD   950
 951  SIDHKFYQQVKNMQLELASLKQISAAFFTRIPLKIKDFKKEINAFNEKGS  1000
1001  LDFQFGRGFVLSSKDRIEREVKNVVEKFDEVNDQIELMRSDVLLRKVRPG  1050
1051  LDQTSQLNEESAYLEKRIQTLERSLEEVTPIWKKQWERELNAIVQEQEFL  1100
1101  DSHTVLISDLKRDLSALSTVLSNVSAIAELQAKSSIKSKPLTLKTATESE  1150
1151  IKGYRDQIQLEVLNLKPDSEARLQAIERSELLQKKRLLQRVDEFSKEVKT  1200
1201  FVENEKLNKIGGAEEADRIRTIQDEKVRKILWDDFVSSKRNGKNGGSFIE  1250
1251  ESSDTVLDEHVVPDNSAKATVAEIDYGSQVDTENFMLERSPLATPKPLKQ  1300
1301  PDFNIYETPIVRSTAHETDDEQTPSKYSDNRVESSSDTVFENTDLKYDNN  1350
1351  VQMSKVTHHVRHDTISTDDYDAYEDAEDVEETSLT                 1385

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.)

Go back to the NucPred Home Page.