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

NucPred

Fetching P49080 from www.uniprot.org...

The NucPred score for your sequence is 0.12 (see score help below)

   1  MQGLAVSCQLPPAAAAARWRPRASSSNREAVLQCWKYELSQDHYLGGPLR    50
51 IGQSQGSLHRHRSTNFLRPAAAAISVEQDEVNTYLPKGDMWSVHKFGGTC 100
101 MGTPKRIQCVANIVLGDSSERKLIIVSAMSKVTDMMYNLVQKAQSRDDSY 150
151 AIALAEVFEKHMTAAKDLLDGEDLARFLSQLHSDVSNLRAMLRAIYIAGH 200
201 ATESFSDFVVGHGELWSAQMLSYAIKKSGAPCSWMDTREVLVVTPSGCNQ 250
251 VDPDYLECEKRLQKWFSRQPAEIIVATGFIASTAGNIPTTLKRDGSDFSA 300
301 AIVGSLVRARQVTIWTDVDGVFSADPRKVSEAVILSTLSYQEAWEMSYFG 350
351 ANVLHPRTIIPVMKDNIPIVIRNMFNLSAPGTMICKQPANENGDLDACVK 400
401 SFATVDNLALVNVEGTGMAGVPGTASAIFSAVKDVGANVIMISQASSEHS 450
451 VCFAVPEKEVAVVSAELHDRFREALAAGRLSKVEVINGCSILAAVGLRMA 500
501 STPGVSAILFDALAKANINVRAIAQGCSEYNITVVLKQQDCVRALRAAHS 550
551 RFFLSKTTLAVGIIGPGLIGGALLNQLKNQTAVLKENMNIDLRVIGITGS 600
601 STMLLSDTGIDLTQWKQLLQKEAEPADIGSFVHHLSDNHVFPNKVLVDCT 650
651 ADTSVASHYYDWLKKGIHVITPNKKANSGPLDQYLKLRTMQRASYTHYFY 700
701 EATVGAGLPIISTLRGLLETGDKILRIEGIFSGTLSYIFNNFEGTRAFSD 750
751 VVAEAREAGYTEPDPRDDLSGTDVARKVVVLARESGLRLELSDIPVKSLV 800
801 PETLASCSSADEFMQKLPSFDEDWARQRSDAEAAGEVLRYVGALDAVNRS 850
851 GQVELRRYRRDHPFAQLSGSDNIIAFTTSRYKEQPLIVRGPGAGAEVTAG 900
901 GVFCDILRLASYLGAPS 917

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.)

Go back to the NucPred Home Page.