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

NucPred

Fetching Q12553 from www.uniprot.org...

The NucPred score for your sequence is 0.38 (see score help below)

   1  MAPGVLLQPSQSELEAASPPKAAASLLQLTEEWDDTIRFYLNGTKVILDS    50
  51  VDPEITLLEYLRGIGLTGTKLGCAEGGCGACTVVVSQINPTTKKLYHASI   100
 101  NACIAPLVAVDGKHVITVEGIGNVKNPHAIQQRLAIGNGSQCGFCTPGIV   150
 151  MSLYALLRNDPKPSEHAVEEAFDGNLCRCTGYRPILDAAQSFTSPIGCGK   200
 201  ARANGGSGCCMEEQKGTNGCCKGSSEETTEDVKHKFASPDFIEYKPDTEL   250
 251  IFPPSLWKHELRPLAFGNKRKKWYRPVTVQQLLEIKSIHPDAKLIGGSTE   300
 301  TQIEIKFKQMRYGASVYLGDLAELRQFAFHDNYLEIGANISLTDLESVCD   350
 351  QAIERYGSARGQPFAAIKKQLRYFAGRQIRNVASPAGNLATASPISDLNP   400
 401  VFVATNTTLVARSLDKETEIPMTQFFRGYRSTALPPDAIISSLRIPTASE   450
 451  KGEYLRAYKQSKRKDDDIAIVNAALRVSLSSSNDVTSVSLVFGGMAPLTV   500
 501  SARNAEAFLTGKKFTDPATLEGTMGALEQDFNLKFGVPGGMATYRKSLAL   550
 551  GFFYRFYHDVLSQIEARSSDLDNSVVAEIERAISTGEKDNEASAAYQQRV   600
 601  LGRAGPHLSALKQATGEAQYTDDIPAQKNELYGCMVLSTKAHAKLLSVNT   650
 651  EAALEIPGVIDYVDHKDLPSPRANWWGAPNCDEVFFAVDKVTTAGQPIGM   700
 701  ILANTAKAAEEGARAVKVEYEELPVILSIEEAIEAQSFFERFRYIKNGDP   750
 751  ESAFRDADHVFEGVSRMGGQEHFYLETQACVAIPKAEDGEMEIWSSTQNP   800
 801  TETQSYVAQVTGVAANKIVSRVKRLGGGFGGKETRSVQLAGICATAAAKV   850
 851  RRPVRCMLNRDEDIATSGQRHPFYCKWKVGVTREGKLLALDADVYANGGH   900
 901  TQDLSGAVVERSLSHIDNVYRFPNIYVRGRICKTNTVSNTAFRGFGGPQG   950
 951  LFFAESIISEVADHLDLQVEQLRILNMYEPGDMTHFNQELKDWHVPLMYD  1000
1001  QVLQESEYFERRKAVEEYNRTHKWSKRGMAIIPTKFGISFTALFLNQAGA  1050
1051  LVHIYHDGSVLVAHGGVEMGQGLHTKMTMIAAEALGVPLSDVFISETATN  1100
1101  TVANTSSTAASASSDLNGYAIYNACTQLNERLKPYREKMPNATLKDLAHA  1150
1151  AYFDRVNLSAQGYYRTPDIGYTWGENKGQMFFYFTQGVTAAEVEIDTLTG  1200
1201  DWTPLRADIKMDVGRTINPSIDYGQIEGAYIQGQGLFTTEESLWHRTTGQ  1250
1251  IFTKGPGNYKIPGFRDIPQIFNVSLLKDVEWENLRTIQRSRGVGEPPLFM  1300
1301  GSAAFFAIRDALKAARKEWGVTDVLSLVSPATPERIRVSCADPIIERARV  1350
1351  KAEEGEKSFFVAI                                       1363

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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