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

NucPred

Fetching Q90240 from www.uniprot.org...

The NucPred score for your sequence is 0.24 (see score help below)

   1  MAGAARGLLWAALSLCLLPEPLRAAHIKKAEAAAAGGGGGVGGELRYLHA    50
  51  AELGQALRDLVAEAPPGLARLFSIGRSVEGRPLWVLRLTAGLPELPEARQ   100
 101  DGEKKKKEEEEEEEEEEGEEGGGGALPGRPQVKLVGNMHGDEPLARPLLL   150
 151  RLAQELVRGWAGGDERLGRLLNTTDLYLLPSLNPDGFERAREGDCGGGGG   200
 201  GGGEGGGEPGGRENSRGRDLNRSFPDQFGSAQPDLEPVPEVRALIAWMRR   250
 251  NKFLLSGNLHGGSVVASYPYDDSPTHRPTGVYSKSADDEVFKYLAKAYAS   300
 301  HHPIMRTGKPNCPGEEGETFQDGITNGAQWYDVEGGMQDYNYVWANCFEI   350
 351  TLELSCCKYPPTSELQQEWENNRESLLTFIEKVHIGVKGFVRDAITGAGL   400
 401  ENATIVVAGIAHNITAGKFGDYHRLLVPGTYNVTAVVMGYAPVTKENIEV   450
 451  KEADATVVDFSLQPTVVAPDPNLTQFTATPAPPSTLTPSVAQVEPPATTS   500
 501  LHQAVQPVDFRHHHFSDMEIFLRRYANEYPSITRLYSVGKSVELRELYVM   550
 551  EISDNPGIHEAGEPEFKYIGNMHGNEVVGRELLLNLIEYLCKNFGTDPEV   600
 601  TDLVQSTRIHIMPSMNPDGYEKSQEGDRGGTVGRNNSNNYDLNRNFPDQF   650
 651  FQVTDPPQPETLAVMSWLKTYPFVLSANLHGGSLVVNYPFDDDEQGIAIY   700
 701  SKSPDDAVFQQLALSYSKENKKMYQGSPCKDLYPTEYFPHGITNGAQWYN   750
 751  VPGGMQDWNYLNTNCFEVTIELGCVKYPKAEELPKYWEQNRRSLLQFIKQ   800
 801  VHRGIWGFVLDATDGRGILNATISVADINHPVTTYKDGDYWRLLVQGTYK   850
 851  VTASARGYDPVTKTVEVDSKGGVQVNFTLSRTDAKVEEGKVPVLNTPDTS   900
 901  DPNEKEFETLIKDLSAENGLERLLLASSGKVSPYRYRPYKDLSEFLRGLY   950
 951  LNYPHITNLTSLGQSVEFRQIWSLEISNKPNHSEPEEPKIRFVAGIHGNA  1000
1001  PVGTELLLALAEFLCMNYKKNSAVTKLIDRTRIVIVPSLNPDGREIAQER  1050
1051  GCTSKLGHANAHGRDLDTDFTSNYSWYSGTREPETKAIIENLILKQDFSL  1100
1101  SVALDGGSLLVTYPFDKPAQTVENKETLKHLASVYANNHPLMHLGQPGCP  1150
1151  NKSDENIPGGVIRGSEWHSHLGSMKDFSVTFGHCPEITVYTSCCYFPSAG  1200
1201  QLPGLWADHRKSLLSMLVEVHKGVHGFVQDKSGKAISKATIVLNEGLRVY  1250
1251  TKEGGYFHVLLAPGLHNINAIADGYQQKHMKVLVRHDAPSSVFIVFDMEN  1300
1301  RIFGLPRELVVTVAGASMSALVLTACIIWCVCSIKSNRHKDGFPTLRQHH  1350
1351  DDYEDEIRMMSTGSKKSLLSHEFQDETDTEEETLYSSKH             1389

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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