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

NucPred

Fetching Q14031 from www.uniprot.org...

The NucPred score for your sequence is 0.27 (see score help below)

   1  MLINKLWLLLVTLCLTEELAAAGEKSYGKPCGGQDCSGSCQCFPEKGARG    50
  51  RPGPIGIQGPTGPQGFTGSTGLSGLKGERGFPGLLGPYGPKGDKGPMGVP   100
 101  GFLGINGIPGHPGQPGPRGPPGLDGCNGTQGAVGFPGPDGYPGLLGPPGL   150
 151  PGQKGSKGDPVLAPGSFKGMKGDPGLPGLDGITGPQGAPGFPGAVGPAGP   200
 201  PGLQGPPGPPGPLGPDGNMGLGFQGEKGVKGDVGLPGPAGPPPSTGELEF   250
 251  MGFPKGKKGSKGEPGPKGFPGISGPPGFPGLGTTGEKGEKGEKGIPGLPG   300
 301  PRGPMGSEGVQGPPGQQGKKGTLGFPGLNGFQGIEGQKGDIGLPGPDVFI   350
 351  DIDGAVISGNPGDPGVPGLPGLKGDEGIQGLRGPSGVPGLPALSGVPGAL   400
 401  GPQGFPGLKGDQGNPGRTTIGAAGLPGRDGLPGPPGPPGPPSPEFETETL   450
 451  HNKESGFPGLRGEQGPKGNLGLKGIKGDSGFCACDGGVPNTGPPGEPGPP   500
 501  GPWGLIGLPGLKGARGDRGSGGAQGPAGAPGLVGPLGPSGPKGKKGEPIL   550
 551  STIQGMPGDRGDSGSQGFRGVIGEPGKDGVPGLPGLPGLPGDGGQGFPGE   600
 601  KGLPGLPGEKGHPGPPGLPGNGLPGLPGPRGLPGDKGKDGLPGQQGLPGS   650
 651  KGITLPCIIPGSYGPSGFPGTPGFPGPKGSRGLPGTPGQPGSSGSKGEPG   700
 701  SPGLVHLPELPGFPGPRGEKGLPGFPGLPGKDGLPGMIGSPGLPGSKGAT   750
 751  GDIFGAENGAPGEQGLQGLTGHKGFLGDSGLPGLKGVHGKPGLLGPKGER   800
 801  GSPGTPGQVGQPGTPGSSGPYGIKGKSGLPGAPGFPGISGHPGKKGTRGK   850
 851  KGPPGSIVKKGLPGLKGLPGNPGLVGLKGSPGSPGVAGLPALSGPKGEKG   900
 901  SVGFVGFPGIPGLPGIPGTRGLKGIPGSTGKMGPSGRAGTPGEKGDRGNP   950
 951  GPVGIPSPRRPMSNLWLKGDKGSQGSAGSNGFPGPRGDKGEAGRPGPPGL  1000
1001  PGAPGLPGIIKGVSGKPGPPGFMGIRGLPGLKGSSGITGFPGMPGESGSQ  1050
1051  GIRGSPGLPGASGLPGLKGDNGQTVEISGSPGPKGQPGESGFKGTKGRDG  1100
1101  LIGNIGFPGNKGEDGKVGVSGDVGLPGAPGFPGVAGMRGEPGLPGSSGHQ  1150
1151  GAIGPLGSPGLIGPKGFPGFPGLHGLNGLPGTKGTHGTPGPSITGVPGPA  1200
1201  GLPGPKGEKGYPGIGIGAPGKPGLRGQKGDRGFPGLQGPAGLPGAPGISL  1250
1251  PSLIAGQPGDPGRPGLDGERGRPGPAGPPGPPGPSSNQGDTGDPGFPGIP  1300
1301  GPKGPKGDQGIPGFSGLPGELGLKGMRGEPGFMGTPGKVGPPGDPGFPGM  1350
1351  KGKAGPRGSSGLQGDPGQTPTAEAVQVPPGPLGLPGIDGIPGLTGDPGAQ  1400
1401  GPVGLQGSKGLPGIPGKDGPSGLPGPPGALGDPGLPGLQGPPGFEGAPGQ  1450
1451  QGPFGMPGMPGQSMRVGYTLVKHSQSEQVPPCPIGMSQLWVGYSLLFVEG  1500
1501  QEKAHNQDLGFAGSCLPRFSTMPFIYCNINEVCHYARRNDKSYWLSTTAP  1550
1551  IPMMPVSQTQIPQYISRCSVCEAPSQAIAVHSQDITIPQCPLGWRSLWIG  1600
1601  YSFLMHTAAGAEGGGQSLVSPGSCLEDFRATPFIECSGARGTCHYFANKY  1650
1651  SFWLTTVEERQQFGELPVSETLKAGQLHTRVSRCQVCMKSL           1691

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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