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

NucPred

Fetching P07547 from www.uniprot.org...

The NucPred score for your sequence is 0.25 (see score help below)

   1  MSNPTKISILGRESIIADFGLWRNYVAKDLISDCSSTTYVLVTDTNIGSI    50
  51  YTPSFEEAFRKAAAEITPSPRLLIYNAPPGEVSKSRQTKADIEDWMLSQN   100
 101  PPCGRDTVVIALGGGVIGDLTGFVASTYMRGVRYVQVPTTLLAMVDSSIG   150
 151  GKTAIDTPLGKNLIGAIWQPTKIYIDLEFLETLPVREFINGMAEVIKTAA   200
 201  ISSEEEFTALEENAETILKAVRREVRPGEHRFEGIEEILKARILASARHK   250
 251  AYVVSADEREGGLRNLLNWGHSIGHAIEAILTPQILHGECVAIGMVKEAE   300
 301  LARHLGILKGVAVSRIVKCLAAYGLPTSLKDARIRKLTAGKHCSVDQLMF   350
 351  NMALDKKNDGPKKKIVLLSAIGTPYETRASVVANEDIRVVLAPSIEVHPG   400
 401  VAQSSNVICAPPGSKSISNRALVLAALGSGTCRIKNLLHSDDTEVMLNAL   450
 451  ERLGAATFSWEEEGEVLVVNGKGGNLQASSSPLYLGNAGTASRFLTTVAT   500
 501  LANSSTVDSSVLTGNNRMKQRPIGDLVDALTANGASIEYVERTGSLPLKI   550
 551  AASGGFAGGNINLAAKVSSQYVSSLLMCAPYAKEPVTLRLVGGKPISQPY   600
 601  IDMTTAMMRSFGIDVQKSTTEEHTYHIPQGRYVNPAEYVIESDASSATYP   650
 651  LAVAAVTGTTCTVPNIGSASLQGDARFAVEVLRPMGCTVEQTETSTTVTG   700
 701  PSDGILRPLPNVDMEPMTDAFLGASVLAAIARGKESNHTTRIYGIANQRV   750
 751  KECNRIKAMKDELAKFGVICREHDDGLEIDGIDRSNLRQPVGGVFCYDDH   800
 801  RVAFSFSVLSLVTPQPTLILEKECVGKTWPGWWDTLRQLFKVKLEGKELE   850
 851  EEPVAASGPDRANASIYIIGMRGAGKSTAGNWVSKALNRPFVDLDTELET   900
 901  VEGMTIPDIIKTRGWQGFRNAELEILKRTLKERSRGYVFACGGGVVEMPE   950
 951  ARKLLTDYHKTKGNVLLLMRDIKKIMDFLSIDKTRPAYVEDMMGVWLRRK  1000
1001  PWFQECSNIQYYSRDASPSGLARASEDFNRFLQVATGQIDSLSIIKEKEH  1050
1051  SFFASLTLPDLREAGDILEEVCVGSDAVELRVDLLKDPASNNDIPSVDYV  1100
1101  VEQLSFLRSRVTLPIIFTIRTQSQGGRFPDNAHDAALELYRLAFRSGCEF  1150
1151  VDLEIAFPEDMLRAVTEMKGFSKIIASHHDPKGELSWANMSWIKFYNKAL  1200
1201  EYGDIIKLVGVARNIDDNTALRKFKNWAAEAHDVPLIAINMGDQGQLSRI  1250
1251  LNGFMTPVSHPSLPFKAAPGQLSATEIRKGLSLMGEIKPKKFAIFGSPIS  1300
1301  QSRSPALHNTLFAQVGLPHNYTRLETTNAQDVQEFIRSPDFGGASVTIPL  1350
1351  KLDIMPLLDEVAAEAEIIGAVNTIIPVSTGKNTPSRLVGRNTDWQGMILS  1400
1401  LRKAGVYGPKRKDQEQSALVVGGGGTARAAIYALHNMGYSPIYIVGRTPS  1450
1451  KLENMVSTFPSSYNIRIVESPSSFESVPHVAIGTIPADQPIDPTMRETLC  1500
1501  HMFERAQEADAEAVKAIEHAPRILLEMAYKPQVTALMRLASDSGWKTIPG  1550
1551  LEVLVGQGWYQFKYWTGISPLYESARACSSPLI                   1583

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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