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

NucPred

Fetching P28040 from www.uniprot.org...

The NucPred score for your sequence is 0.98 (see score help below)

   1  MRKRNAGIKPSQRFAELRALRQAGKTRASTYESKENEELYDNVSEEEYRK    50
  51  IVRQRLDEDDFVVDDNGAGYVDNGYDEWDQSHYSDEDDENEKGSSGRKRK   100
 101  KSKNVLAEPNQQIGAFFKANAIQPASRIANRKNNEKEDEFMAEILGSIDQ   150
 151  DIPERLSTKKGNRSHTTSNAKRRSQKAASSISTTNVVSSDPKKYIPETVP   200
 201  STPQPASSLPIPSSPPAALETEENVDSQPMELDEPELPVGSDAPIIDVEE   250
 251  SIAMKPLMSHDQVDDTASLSKATISQQPLSPMTPLSSELDVSAFSEINSK   300
 301  IKNVDVPASSYSSPISKVSPSDVTEEDGSLFFFWMDYTEMYGSLCLFGKV   350
 351  YDKATKQYVSCFLKVDGIMRSLYFLPRPSSSSVSEDSIAAQTKDVYDEVA   400
 401  NLLSKRGVKEWKSRVSKYKYAFELEDVPRTADYLEVIYSYSYPALPTDLT   450
 451  GSSFSHVFGTNTALFEQFVLSRRVMGPCWLKIQQPNFDAVKNASWCRVEI   500
 501  GCSSPQNISVSFEKNEITSKTPPMTVMSLAFRTLINKEQNKQEVVMISAR   550
 551  IFENVDIEKGLPANDMPSYSFSLIRPLKQIFPNGFEKLARQHKSSIFCER   600
 601  SEVSLLNNFLNKVRTYDPDVYFGHDFEMCYSVLLSRLKERKIHNWSSIGR   650
 651  LRRSEWPRSFNRSSQQFVEKQIIAGRLMCDLSNDFGRSMIKAQSWSLSEI   700
 701  VLKELDIKRQDINQEKALQSWTDTAHGLLDYLVHCEIDTFFIAAVAFKIQ   750
 751  MLQLSKNLTNIAGNSWARTLTGTRAERNEYILLHEFKKNGYIVPDKQQSI   800
 801  RRHAEAFGAEDGLQEESLGKKKDKYKGGLVFEPQKGLYETCILVMDFNSL   850
 851  YPSIIQEYNICFTTVDRSPSNSDSDDQIPDTPSASANQGIFPRLIANLVE   900
 901  RRRQIKGLLKDNSATPTQRLQWDIQQQALKLTANSMYGCLGYTKSRFYAR   950
 951  PLAVLITYKGREALMNTKELADQMGLQVIYGDTDSVMLNTNVTDKNHALR  1000
1001  IGNEFKEKVNERYSKLEIDIDNVYQRMLLHAKKKYAALQLDSQGKPNLDV  1050
1051  KGLDMKRREFCTLAKEASKFCLDQILSGELTETVIENIHSYLMDFSEKMR  1100
1101  NGKFPANKFIIFNRLGKNPEDYPNGKTMPFVQVALKKKARGENVRVGDVI  1150
1151  PFIIAGSDADGHPADRAYSPQEIMNTNSTLVIDYNYYLSHQILPPIERVI  1200
1201  APIEGTNRARLAECLGLDARKYYSHETSESSAFQRYESTLTDDQCFINVS  1250
1251  PLLLKCPSCNATSFSLRSVKSLKETLYANTVECDCGYEYSDFTIILQFSS  1300
1301  QLRDFINLYYEGILVCDDSSCGNRTRQMSVYGKRCCNKSCRGSVHFEYND  1350
1351  EQLYNQIKFLLKAVQTTTGATRNGIIRCNAINKNISRIMNKNAREFVDMG  1400
1401  LIFSS                                               1405

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.)

Go back to the NucPred Home Page.