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

NucPred

Fetching Q6FLB1 from www.uniprot.org...

The NucPred score for your sequence is 0.96 (see score help below)

   1  MSDQESASLREEKNEIINGMGSGAPSDEEEGEDVFDSSEEEEEDDEDEAR    50
  51  KISEGFIVNDEDEDEDEDDENVADKKKKRRHKRRAREEEDDRLSEDDLDL   100
 101  LMENAGVKRPTTEGSSGGKLKRLKRVGDEVESGAADREQESSQEKESSRL   150
 151  NDFFSDDEDEEPYDEENRERSRGSREYDRGESNHQGDNRKSGMLDELDDF   200
 201  IEEDEFSDEDEETRQQRLLERKMMREQRMKAPTKITGLSSDKIDEMYDVF   250
 251  GDGHDYDWALEIENEELEGGDINEQSEEFDEETGMTKSSKKKISLQDIYD   300
 301  LQDLKKNLMTDEDMLIRKTDIPERYQELRSGLVNHGNLSDNDQELEKNWI   350
 351  SEKIAVDKNFSADYDLTEFKEAVGNAIKFITKENLEVPFIYAYRRNYISS   400
 401  RERDGFLLTEDDLWEIVHLDIEFQSIINKRDYVKRFYSELGISDPLVDEY   450
 451  FKNQSTGSVAELNSLQDIYNYLEFKYAQEINDNLQKESDKSGKKHLKNSN   500
 501  YEKFKSSALYKVIEAVGVSADQIGNNISSQHQIHIPKDHEALKPLELIEL   550
 551  VLNENAGDLQVFLSNIKLAMDTIQKYYSWEISKNTKVREKVRADFYRYYL   600
 601  VDVVLTTKGKREIQRGSLYEDIKYAINRTPLHFRREPEIFLKMLEAESLN   650
 651  LMTLKLHMSSQKQYVDHLFQIALETTNTSDLAIEWNNFRKAAFTQAIEKI   700
 701  FNDIAQEIKDDLEKTCQKLVCKVVRHKFMTKLDQAPYVPDLKDPKLPKIL   750
 751  TLTCGQGRFGSDAIIAAYVNRKGEFVRDFKITENPFDRSNPDKFEEVFED   800
 801  IVQTCQITAIGINGPNPKTQKLFKKLIEVIHKKNLVDSKGTHIPIIYVED   850
 851  EIAIRYQNSERAAQEFPNKPPYVKYCIALARYMHSPLMEYANLSPEELKS   900
 901  LSIHPFQSFLSPEYLNRAIETAFVDIVNLVGVEVNKATDNSYYASVLRFV   950
 951  SGFGKRKAIDFLESLQRLNEPLLARQQLITHNILHKVIFMNSAGFLYISW  1000
1001  SKKRQRYEDLEHDQLDSTRIHPEDYHLATKVAADALEYDPDTIAEKEENG  1050
1051  TMSEFIEFLREDPNRRSKLESLNLESYAEELEKNTGQRKLNNLNTIVLEL  1100
1101  LDGFEELRNDFHIMQSEEVFSSLTGETDKTLFKGCVIPVRVERFWHNDIV  1150
1151  CVTNSEVECIVNAQRHLGAQVRRPPNEIYELNKTYPAKVIFIDYPNITAE  1200
1201  VSLLEHDVKNEYNPLTYSKDPAIWDLKQELEDSEEEKKVTMAESRAKRTH  1250
1251  RVINHPYYFPFNGKQAEDYLRSKERGDFVIRQSSRGDDHLAITWKLDKDL  1300
1301  FQHVDIQELEKENPLALGKVLVVEGQRYHDLDQIIVEYLQNKIRLLNELT  1350
1351  SNEKFKAGTKKEVVKFIEDYSKVNPKKSVYYFSLNYENPGWFYLIFKLNA  1400
1401  ESKLYIWNVKLTHTGFFLVNYNYPTVIQLCNGFKTLLKSSNTRNRSGYR   1449

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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