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

NucPred

Fetching Q03214 from www.uniprot.org...

The NucPred score for your sequence is 0.78 (see score help below)

   1  MSGHDSVTKISHILNEPVNEKVMVQNGFHESSKIADIELEIQERPSIKQW    50
  51  ESPRSAVIPTSNHNFSPFLYTQFKSRGAAPFAPETIKSVDLVELPEGVPA   100
 101  RVFHEKTGLFYQISPHSIPTFILAKKELPDPIKFYELVEDLGSVYGCVKL   150
 151  KIIPDADKFTQLNVDVDRLWFKARKQFFNSNEFQRTKIVDFYAKLYNFHN   200
 201  KIKKSTLTRIPSIDKRTLDLYRLRSCVKLRGGFNAVCEKKLWAQIGRELG   250
 251  YSGRIMSSLSTSLRSAYAKILLDFDIYEEEEQAARNNEKNEDMVESEIFR   300
 301  HSNSRSRDEEEPLHKKAKIHRDVFRAGSINHEFKRMRDIKHIKGFPTYFN   350
 351  SLTEFKLGYTQSTETTLPGYDFTFWENGMEIYDKSKYETKTSPVYNLRQY   400
 401  YEKSLAVFTAIVAKFGSSYPDLFAKHTTLPQKEFERLYFHLLSEHFIDFE   450
 451  IDTGLGLPCSMRSPGNNSSNEKFAIKNILDQWNLDNIPLNELSLLQHLDL   500
 501  DMANFTRTTYDIGMLFSCQGWSVSDHFLPSIDFNHLGSTKLVYSIAPKDM   550
 551  EKFEALIARGKSEWDTIQSRPRYSTSDDELKSFIETDFYKSFLDAEQSAD   600
 601  YSNTGDNSKNSFPEDKIAGNTLHDGSQSDFIFEPNFILANGIKLYKTTQE   650
 651  QGSYIFKFPKAFTCSIGSGFYLSQNAKFAPSSWLRFSSEAAKWTSKMGFL   700
 701  PGLDVNQLLINALLNSNNPVLRKKCRDLISNYVVEEAENSKKLGELIGTV   750
 751  DVVYNKLNYISDISLESTGLSKIVVTHGALQRNLSLKEFVVLLEKPENGA   800
 801  HSICGIPIRDQSGNLNVCLHSYFDSASLGIALDGLDKPPTSYLLVHNEDF   850
 851  EKKWDVLMTSTFRNRTVPLNIIQYLISHTDSNTEFNRMLRSNFDDSLLLI   900
 901  EKCKKFIKTFVDVSCSVKDVDFGNGFNLRHLPLKFSDNMADNLESLYESV   950
 951  RKCSIEFSEKPTIIRLYHVSRQFPIDNRDIIDGNNLDLLKELYQKSLTIP  1000
1001  LKVSYWTKLTRKICRLEWLSVYEHIFIERCDIKNEDPAKYSLPLLYSYFE  1050
1051  FGLKYCDSEDIDKLGEVRKLILKYQDMMQKVRVFLKKDPPSKISLSDLED  1100
1101  VLLDIEEYRLPIQSSFFSELDYVIREIENAKKMNDVNILYNTDNIDKIDE  1150
1151  LIRKNDPKFVKFANQFNGSRLDKRPLASDNSGSVKAKQELKVFKLWNQHL  1200
1201  DQIMQKNKFIEILPSIFRCLDLKSDKYIPLESCSKRQTKYCFCRRVEEGT  1250
1251  AMVECEICKEWYHVDCISNGELVPPDDPNVLFVCSICTPPCMAVDNIEGV  1300
1301  TFELDDLKRILVESLKLSLIPDPPILKNLFDVFAFALNFKNEMEKELFTN  1350
1351  GYVNQLSSTHKIKYYLRKLKGSQCGFTNLTDPLRKHCQVKDAEAIKWLTD  1400
1401  NGRIIITGIPN                                         1411

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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