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

NucPred

Fetching P02459 from www.uniprot.org...

The NucPred score for your sequence is 0.31 (see score help below)

   1  MIRLGAPQTLVLLTLLVAAVLRCHGQDVQKAGSCVQDGQRYNDKDVWKPE    50
  51  PCRICVCDTGTVLCDDIICEDMKDCLSPETPFGECCPICSADLPTASGQP   100
 101  GPKGQKGEPGDIKDIVGPKGPPGPQGPAGEQGPRGDRGDKGEKGAPGPRG   150
 151  RDGEPGTPGNPGPPGPPGPPGPPGLGGNFAAQMAGGFDEKAGGAQMGVMQ   200
 201  GPMGPMGPRGPPGPAGAPGPQGFQGNPGEPGEPGVSGPMGPRGPPGPPGK   250
 251  PGDDGEAGKPGKSGERGPPGPQGARGFPGTPGLPGVKGHRGYPGLDGAKG   300
 301  EAGAPGVKGESGSPGENGSPGPMGPRGLPGERGRTGPAGAAGARGNDGQP   350
 351  GPAGPPGPVGPAGGPGFPGAPGAKGEAGPTGARGPEGAQGPRGEPGTPGS   400
 401  PGPAGAAGNPGTDGIPGAKGSAGAPGIAGAPGFPGPRGPPGPQGATGPLG   450
 451  PKGQTGEPGIAGFKGEQGPKGEPGPAGPQGAPGPAGEEGKRGARGEPGGA   500
 501  GPAGPPGERGAPGNRGFPGQDGLAGPKGAPGERGPSGLAGPKGANGDPGR   550
 551  PGEPGLPGARGLTGRPGDAGPQGKVGPSGAPGEDGRPGPPGPQGARGQPG   600
 601  VMGFPGPKGANGEPGKAGEKGLPGAPGLRGLPGKDGETGAAGPPGPAGPA   650
 651  GERGEQGAPGPSGFQGLPGPPGPPGEGGKPGDQGVPGEAGAPGLVGPRGE   700
 701  RGFPGERGSPGSQGLQGARGLPGTPGTDGPKGAAGPAGPPGAQGPPGLQG   750
 751  MPGERGAAGIAGPKGDRGDVGEKGPEGAPGKDGGRGLTGPIGPPGPAGAN   800
 801  GEKGEVGPPGPAGTAGARGAPGERGETGPPGPAGFAGPPGADGQPGAKGE   850
 851  QGEAGQKGDAGAPGPQGPSGAPGPQGPTGVTGPKGARGAQGPPGATGFPG   900
 901  AAGRVGPPGSNGNPGPPGPPGPSGKDGPKGARGDSGPPGRAGDPGLQGPA   950
 951  GPPGEKGEPGDDGPSGPDGPPGPQGLAGQRGIVGLPGQRGERGFPGLPGP  1000
1001  SGEPGKQGAPGASGDRGPPGPVGPPGLTGPAGEPGREGSPGADGPPGRDG  1050
1051  AAGVKGDRGETGAVGAPGAPGPPGSPGPAGPIGKQGDRGEAGAQGPMGPA  1100
1101  GPAGARGMPGPQGPRGDKGETGEAGERGLKGHRGFTGLQGLPGPPGPSGD  1150
1151  QGASGPAGPSGPRGPPGPVGPSGKDGANGIPGPIGPPGPRGRSGETGPAG  1200
1201  PPGNPGPPGPPGPPGPGIDMSAFAGLGQREKGPDPLQYMRADEAAGNLRQ  1250
1251  HDAEVDATLKSLNNQIESLRSPEGSRKNPARTCRDLKLCHPEWKSGDYWI  1300
1301  DPNQGCTLDAMKVFCNMETGETCVYPNPASVPKKNWWSSKSKDKKHIWFG  1350
1351  ETINGGFHFSYGDDNLAPNTANVQMTFLRLLSTEGSQNITYHCKNSIAYL  1400
1401  DEAAGNLKKALLIQGSNDVEIRAEGNSRFTYTVLKDGCTKHTGKWGKTMI  1450
1451  EYRSQKTSRLPIIDIAPMDIGGPEQEFGVDIGPVCFL               1487

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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