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

NucPred

Fetching P34751 from www.uniprot.org...

The NucPred score for your sequence is 0.74 (see score help below)

   1  MSEKGETLIEDTAEIEFEQTVDKTQQWGRLKNAAAFSLFRDLHMNESLQR    50
51 KHARSDYKVYDLNNRVIFHVINTTAMPITKDGPFCLKVMNKDKKSVAKFL 100
101 RNEPKRSYKQTGLASLFGCCSDTEDTMEVLDDNGLIIATSFLHHDQFRGI 150
151 LITMKDPAGKVLIGIQASRDQKDVFAVSGPDNRYLGEIRQKIISSGNSTD 200
201 NYKGVACWFSTEVSLNVKVFFMAAAFLIEIDYFSETKSRQAPFRTPEADY 250
251 LNPIIKTPPHNERVPKMKTNISKTRKKKGKVSDASKDSRPSETKKETLMM 300
301 PEIHHTKHFDSIGGEEQAFAKKEKVEEFKPTEAVKEEVDVNGMSRDQFRN 350
351 AAKKVVDYLMKQDESIRAARCSPALKPGYLKALLPPKAPQKAEDIDDILE 400
401 DYHKLIVPGLSHSSHPNFHSFYPAGNSFHCLLADLLGGHIGDAGFYWTSN 450
451 PALTELEVLMMDWLGEMMALPKEFLLFPEASRGGGCMQRSDTESNFLVLV 500
501 AARTDMIRRMKQRDKRLRSSDILARLVAYTSSDARRSIKMKMAAEVAMVK 550
551 MRVLPTDQNFILRGDTLHAAIMADIERGLIPFFVGANFGTSGPCSFDHLH 600
601 ELGPVCREHGTWLHVDAAYAGTALICPEIRGLMRGIDWADSFCTTPSKLI 650
651 IAVCDVCCLWVRDRHKLQHASLENHPDLPFKGLPTSQRVGALKIWFMIRS 700
701 FGVENLQNQIREHIRLGQVMTKILQKDLRFEVCNKVVMGLICFRAKSNDM 750
751 FNKALLYRCNETGNVSLASCVLQNKFVIRMCINSPKCSEEDLDSAYKLIC 800
801 NEYDILKPFQYRIEVMNQAELETFIRDPAKIHSSAEVSRRFPVVNPLEPC 850
851 RSLAQISSQMHTAEYADPPGKSNKSPQVAAKGELPSAAPPSSRTPNSDIS 900
901 EKSDR 905

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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