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

NucPred

Fetching P04412 from www.uniprot.org...

The NucPred score for your sequence is 0.47 (see score help below)

   1  MLLRRRNGPCPFPLLLLLLAHCICIWPASAARDRYARQNNRQRHQDIDRD    50
  51  RDRDRFLYRSSSAQNRQRGGANFALGLGANGVTIPTSLEDKNKNEFVKGK   100
 101  ICIGTKSRLSVPSNKEHHYRNLRDRYTNCTYVDGNLKLTWLPNENLDLSF   150
 151  LDNIREVTGYILISHVDVKKVVFPKLQIIRGRTLFSLSVEEEKYALFVTY   200
 201  SKMYTLEIPDLRDVLNGQVGFHNNYNLCHMRTIQWSEIVSNGTDAYYNYD   250
 251  FTAPERECPKCHESCTHGCWGEGPKNCQKFSKLTCSPQCAGGRCYGPKPR   300
 301  ECCHLFCAGGCTGPTQKDCIACKNFFDEAVSKEECPPMRKYNPTTYVLET   350
 351  NPEGKYAYGATCVKECPGHLLRDNGACVRSCPQDKMDKGGECVPCNGPCP   400
 401  KTCPGVTVLHAGNIDSFRNCTVIDGNIRILDQTFSGFQDVYANYTMGPRY   450
 451  IPLDPERREVFSTVKEITGYLNIEGTHPQFRNLSYFRNLETIHGRQLMES   500
 501  MFAALAIVKSSLYSLEMRNLKQISSGSVVIQHNRDLCYVSNIRWPAIQKE   550
 551  PEQKVWVNENLRADLCEKNGTICSDQCNEDGCWGAGTDQCLTCKNFNFNG   600
 601  TCIADCGYISNAYKFDNRTCKICHPECRTCNGAGADHCQECVHVRDGQHC   650
 651  VSECPKNKYNDRGVCRECHATCDGCTGPKDTIGIGACTTCNLAIINNDAT   700
 701  VKRCLLKDDKCPDGYFWEYVHPQEQGSLKPLAGRAVCRKCHPLCELCTNY   750
 751  GYHEQVCSKCTHYKRREQCETECPADHYTDEEQRECFQRHPECNGCTGPG   800
 801  ADDCKSCRNFKLFDANETGPYVNSTMFNCTSKCPLEMRHVNYQYTAIGPY   850
 851  CAASPPRSSKITANLDVNMIFIITGAVLVPTICILCVVTYICRQKQKAKK   900
 901  ETVKMTMALSGCEDSEPLRPSNIGANLCKLRIVKDAELRKGGVLGMGAFG   950
 951  RVYKGVWVPEGENVKIPVAIKELLKSTGAESSEEFLREAYIMASEEHVNL  1000
1001  LKLLAVCMSSQMMLITQLMPLGCLLDYVRNNRDKIGSKALLNWSTQIAKG  1050
1051  MSYLEEKRLVHRDLAARNVLVQTPSLVKITDFGLAKLLSSDSNEYKAAGG  1100
1101  KMPIKWLALECIRNRVFTSKSDVWAFGVTIWELLTFGQRPHENIPAKDIP  1150
1151  DLIEVGLKLEQPEICSLDIYCTLLSCWHLDAAMRPTFKQLTTVFAEFARD  1200
1201  PGRYLAIPGDKFTRLPAYTSQDEKDLIRKLAPTTDGSEAIAKPDDYLQPK  1250
1251  AAPGPSHRTDCTDEMPKLNRYCKDPSNKNSSTGDDERDSSAREVGVGNLR  1300
1301  LDLPVDEDDYLMPTCQPGPNNNNNMNNPNQNNMAAVGVAAGYMDLIGVPV  1350
1351  SVDNPEYLLNAQTLGVGESPIPTQTIGIPVMGGPGTMEVKVPMPGSEPTS  1400
1401  SDHEYYNDTQRELQPLHRNRNTETRV                          1426

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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