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

NucPred

Fetching Q7PC81 from www.uniprot.org...

The NucPred score for your sequence is 0.64 (see score help below)

   1  MTMPQTDGVEFASRNNLENGDGDQVRSQWVAIERSPTCKRITTALFCKRD    50
  51  EQGKRSQRRVMDVSKLEDLDRRLFIDELIRHVEDDNRVLLQKIRTRTDEV   100
 101  GIDLPKIEVRFSDLFVEAECEVVHGKPIPTLWNAIASKLSRFTFSKQEDK   150
 151  ISILKGVSGIIRPKRMTLLLGPPGCGKTTLLLALSGRLDPSLKTRGEVSY   200
 201  NGHLFSEFVPEKTSSYVSQNDLHIPELSVRETLDFSGCFQGAGSRLEMMK   250
 251  EISRREKLKGIVPDPDIDAYMKAASIEGSKTNLQTDYILKILGLTICADT   300
 301  RVGDASRPGISGGQKRRLTTGEMIVGPIKTLFMDEISNGLDSSTTFQILS   350
 351  CLQQFARLSEGTILVSLLQPAPETFELFDDLILMGEGKIIYHGPRDFICS   400
 401  FFEDCGFKCPQRKSVAEFLQEVISRKDQEQYWCHRDKPYCYVSIDSFIEK   450
 451  FKKSDLGLQLQDELSKTYDKSQTQKDGLCIRKYSLSNWDMFKACSRREFL   500
 501  LMKRNSFVYVFKSGLLIFIGSIAMTVYLRTGSTRDSLHANYLLGSLFFSL   550
 551  IKLLADGLPELTLTVSRIAVFCKQKELYFYPAWAYAIPSAILKIPISFLE   600
 601  SFLWTMLTYYVIGYSPEAGRFIRQVLILFALHLSCISMFRAIGAVFRDFD   650
 651  VATTIGSISIVLLSVFGGFIVRKPSMPSWLEWGFWLSPLSYAEIGLTSNE   700
 701  FFAPMWRKMTSENRTLGEQVLDARGLNFGNQSYWNAFGALIGFTLFFNTV   750
 751  FALALTFLKTSQRSRVIVSHDKNTQSSEKDSKIASHSKNALPFEPLTFTF   800
 801  QDVQYFIETPQGKKLQLLSDVTGAFKPGVLTALMGVSGAGKTTLLDVLSG   850
 851  RKTRGDIKGQIEVGGYVKVQDTFSRVSGYCEQFDIHSPNLTVQESLKYSA   900
 901  WLRLPCNISSETKSAIVNEVLETIELEEIKDSLVGVPGISGVTAEQRKRL   950
 951  TIAVELVSNPSIIFMDEPTTGLDARAAAIVMRAVKNIAETGRTVVCTIHQ  1000
1001  PSIDIFEAFDELILMKNGGKIIYYGPLGQHSSKVIEYFMSIPGVPKLKEN  1050
1051  SNPATWILDITSKSSEDKLGVDLAHIYEESTLFKENKMVIEQTRCTSLGS  1100
1101  ERLILSSRYAQTSWEQFKACLWKQHLSYWRNPSYNLTRIIFMCFTCMLCG  1150
1151  ILFLQKAKEINNQQDLFNVFGSMFTVVLFSGINNCSTVIFCVATERNVFY  1200
1201  RERFSRMYNPWAYSLAQVLVEIPYSLFQSIIYVIIVYPMVGYHWSVYKVF  1250
1251  WSFYSIFCSLLIFNYFGMLLVVVTPNVHIAFTLRSSFYAIVNLFAGYVMP  1300
1301  KPNIPRWWIWMYYLSPTSWVLNGLLTSQYGDMEKEILAFGEKKKVSAFLE  1350
1351  DYFGYRYDSLALVAVVLIAFPILLASLFAFFIGKLNFQKK            1390

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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