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

NucPred

Fetching Q9N4C2 from www.uniprot.org...

The NucPred score for your sequence is 0.56 (see score help below)

   1  MYGYLRETDDSTAINFSAYGKFLPGENTGFQLLTIGAKFIRIFRVNPYVL    50
  51  KEPGEDNEEWQQKTKLECMFSCRLLNKCHSIAVARVPQLPDQDSILMTFD   100
 101  DAKLSIVSINEKERNMQTISLHAFENEYLRDGFINHFQPPLVRSDPSNRC   150
 151  AACLVYGKHIAILPFHENSKRIHSYVIPLKQIDPRLDNIADMVFLDGYYE   200
 201  PTILFLYEPIQTTPGRACVRYDTMCIMGVSVNIVDRQFAVVWQTANLPMD   250
 251  CSQLLPIPKPLGGALVFGSNTVVYLNQAVPPCGLVLNSCYDGFTKFPLKD   300
 301  LKHLKMTLDCSTSVYMEDGRIAVGSRDGDLFLLRLMTSSGGGTVKSLEFS   350
 351  KVYETSIAYSLTVCAPGHLFVGSRLGDSQLLEYTLLKTTRDCAVKRLKID   400
 401  NKDPAAAEIELDEDDMELYGGAIEEQQNDDDEQIDESLQFRELDRLRNVG   450
 451  PVKSMCVGRPNYMSNDLVDAKRRDPVFDLVTASGHGKNGALCVHQRSLRP   500
 501  EIITSSLLEGAEQLWAVGRKENESHKYLIVSRVRSTLILELGEELVELEE   550
 551  QLFVTGEPTVAAGELSQGALAVQVTSTCIALVTDGQQMQEVHIDSNFPVI   600
 601  QASIVDPYVALLTQNGRLLLYELVMEPYVQLREVDISATSFATWHATAQN   650
 651  LTQLTSISIYADASEIMKFAAAEKSMGGGGGGDGEVSTAENAMMKKEQHE   700
 701  EAILLHGEDDDFLYGDEDETIMEQNFPVENGEATIKQSNTRKRKRLGHDA   750
 751  IQSSRGGEQSDAIDPTRTFSSISHWLIVSHENGRLSIHSLPEMEVVYQIG   800
 801  RFSNVPELLVDLTVEEEEKERKAKAQQAAKEASVPTDEAEQLNTEMKQLC   850
 851  ERVLEAQIVGMGINQAHPILMAIVDEQVVLYEMFSSSNPIPGHLGISFRK   900
 901  LPHFICLRTSSHLNSDGKRAPFEMKINNGKRFSLIHPFERVSSVNNGVMI   950
 951  VGAVPTLLVYGAWGGMQTHQMTVDGPIKAFTPFNNENVLHGIVYMTQHKS  1000
1001  ELRIARMHPDFDYEMPYPVKKIEVGRTIHHVRYLMNSDVYAVVSSIPKPS  1050
1051  NKIWVVMNDDKQEEIHEKDENFVLPAPPKYTLNLFSSQDWAAVPNTEISF  1100
1101  EDMEAVTACEDVALKSESTISGLETLLAMGTVNNYGEEVLVRGRIILCEV  1150
1151  IEVVPEPDQPTSNRKIKVLFDKEQKGPVTGLCAINGLLLCGMGQKVFIWQ  1200
1201  FKDNDLMGISFLDMHYYVYQLHSLRTIAIACDARESMSLIRFQEDNKAMS  1250
1251  IASRDDRKCAQPPMASQLVVDGAHVGFLLSDETGNITMFNYAPEAPESNG  1300
1301  GERLTVRAAINIGTNINAFVRLRGHTSLLQLNNEDEKEAIEQRMTTVFAS  1350
1351  LDGSFGFVRPLTEKSYRRLHFLQTFIGSVTPQIAGLHIKGSRSAKPSQPI  1400
1401  VNGRNARNLIDGDVVEQYLHLSLYDKTDLARRLGVGRYHIIDDLMQLRRM  1450
1451  AFYY                                                1454

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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