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

NucPred

Fetching P70587 from www.uniprot.org...

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

   1  MTTKRKLIGRLVPCRCFRGEEEIISVLDYSHCSLQQVPKEVFNFERTLEE    50
  51  LYLDANQIEELPKQLFNCQALRKLSIPDNDLSSLPTSIASLVNLKELDIS   100
 101  KNGVQEFPENIKCCKCLTIIEASVNPISKLPDGFTQLLNLTQLYLNDAFL   150
 151  EFLPANFGRLVKLRILELRENHLKTLPKSMHKLAQLERLDLGNNEFSELP   200
 201  EVLDQIQNLRELWMDNNALQVLPGSIGKLKMLVYLDMSKNRIETVDMDIS   250
 251  GCEALEDLLLSSNMLQQLPDSIGLLKKLTTLKVDDNQLTMLPNTIGNLSL   300
 301  LEEFDCSCNELESLPPTIGYLHSLRTLAVDENFLPELPREIGSCKNVTVM   350
 351  SLRSNKLEFLPEEIGQMQRLRVLNLSDNRLKNLPFSFTKLKELAALWLSD   400
 401  NQSKALIPLQTEAHPETKQRVLTNYMFPQQPRGDEDFQSDSDSFNPTLWE   450
 451  EQRQQRMTVAFEFEDKKEDDESAGKVKALSCQAPWDRGQRGITLQPARLS   500
 501  GDCCTPWARCDQQIQDMPVPQSDPQLAWGCISGLQQERSMCAPLPVAAQS   550
 551  TTLPSLSGRQVEINLKRYPTPYPEDLKNMVKSVQNLVGKPSHGVRVENAN   600
 601  PTANTEQTVKEKFEHKWPVAPKEITVEDSFVHPANEMRIGELHPSLAETP   650
 651  LYPPKLVLLGKDKKESTDESEVDKTHCLNNSVSSGTYSDYSPSQASSASS   700
 701  NTRVKVGSLQPTTKDAVHNSLWGNRIAPPFPQPLDAKPLLTQREAVPPGN   750
 751  LPQRPDRLPMSDAFPDNWTDGSHYDNTGFVSEEATGENANNNPLLSSKAR   800
 801  SVPAHGRRPLIRQERIVGVPLELEQSTHRHTPETEVPPSNPWQNWTRTPS   850
 851  PFEDRTAFPSKLETTPTTSPLPERKDHMKEPTETPGPFSPGVPWEYHDPT   900
 901  PNRSLGNVFSQIHCRPDSSKGVIAISKSTERLSPLMKDIKSNKFKKSQSI   950
 951  DEIDVGTYKVYNIPLENYASGSDHLGSHERPDKFLGPEHGMSSMSRSQSV  1000
1001  PMLDDEMLMYGSSKGPPQQKASMTKKVYQFDQSFNPQGAVEVKAEKRIPP  1050
1051  PFAHNSEYVQQPGKNIAKDLVSPRAYRGYPPMEQMFSFSQPSVNEDAMVN  1100
1101  AQFASQGPRAGFLRRADSLASSTEMAMFRRVSEPHELPPGDRYGRAAYRG  1150
1151  GLEGQSSVSMTDPQFLKRNGRYEDEHPSYQEVKAQAGSFPAKNLTQRRPL  1200
1201  SARSYSTESYGASQTRPVSARPTMAALLEKIPSDYNLGNYGDKTSDNSDI  1250
1251  KTRPTPVKGEESCGKMPADWRQQLLRHIEARRLDRTPSQQSNILDNGQED  1300
1301  VSPSGQWNPYPLGRRDVPPDTITKKAGSHIQTLMGSQSLQHRSREQQPYE  1350
1351  GNINKVTIQQFQSPLPIQIPSSQATRGPQPGRCLIQTKGQRSMDGYPEQF  1400
1401  CVRIEKNPGLGFSISGGISGQGNPFKPSDKGIFVTRVQPDGPASNLLQPG  1450
1451  DKILQANGHSFVHMEHEKAVLLLKSFQNTVDLVIQRELTV            1490

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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