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

NucPred

Fetching P02457 from www.uniprot.org...

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

   1  MFSFVDSRLLLLIAATVLLTRGEGEEDIQTGSCVQDGLTYNDKDVWKPEP    50
  51  CQICVCDSGNILCDEVICEDTSDCPNAEIPFGECCPICPDVDASPVYPES   100
 101  AGVEGPKGDTGPRGDRGLPGPPGRDGIPGQPGLPGPPGPPGPPGLGGNFA   150
 151  PQMSYGYDEKSAGVAVPGPMGPAGPRGLPGPPGAPGPQGFQGPPGEPGEP   200
 201  GASGPMGPRGPAGPPGKNGDDGEAGKPGRPGQRGPPGPQGARGLPGTAGL   250
 251  PGMKGHRGFSGLDGAKGQPGPAGPKGEPGSPGENGAPGQMGPRGLPGERG   300
 301  RPGPSGPAGARGNDGAPGAAGPPGPTGPAGPPGFPGAAGAKGETGPQGAR   350
 351  GSEGPQGSRGEPGPPGPAGAAGPAGNPGADGQPGAKGATGAPGIAGAPGF   400
 401  PGARGPSGPQGPSGAPGPKGNSGEPGAPGNKGDTGAKGEPGPAGVQGPPG   450
 451  PAGEEGKRGARGEPGPAGLPGPAGERGAPGSRGFPGADGIAGPKGPPGER   500
 501  GSPGAVGPKGSPGEAGRPGEAGLPGAKGLTGSPGSPGPDGKTGPPGPAGQ   550
 551  DGRPGPAGPPGARGQAGVMGFPGPKGAAGEPGKPGERGAPGPPGAVGAAG   600
 601  KDGEAGAQGPPGPTGPAGERGEQGPAGAPGFQGLPGPAGPPGEAGKPGEQ   650
 651  GVPGNAGAPGPAGARGERGFPGERGVQGPPGPQGPRGANGAPGNDGAKGD   700
 701  AGAPGAPGNEGPPGLEGMPGERGAAGLPGAKGDRGDPGPKGADGAPGKDG   750
 751  LRGLTGPIGPPGPAGAPGDKGEAGPPGPAGPTGARGAPGDRGEPGPPGPA   800
 801  GFAGPPGADGQPGAKGETGDAGAKGDAGPPGPAGPTGAPGPAGZVGAPGP   850
 851  KGARGSAGPPGATGFPGAAGRVGPPGPSGNIGLPGPPGPAGKZGSKGPRG   900
 901  ETGPAGRPGEPGPAGPPGPPGEKGSPGADGPIGAPGTPGPQGIAGQRGVV   950
 951  GLPGQRGERGFPGLPGPSGEPGKQGPSGASGERGPPGPMGPPGLAGPPGE  1000
1001  AGREGAPGAEGAPGRDGAAGPKGDRGETGPAGPPGAPGAPGAPGPVGPAG  1050
1051  KNGDRGETGPAGPAGPPGPAGARGPAGPQGPRGDKGETGEQGDRGMKGHR  1100
1101  GFSGLQGPPGPPGAPGEQGPSGASGPAGPRGPPGSAGAAGKDGLNGLPGP  1150
1151  IGPPGPRGRTGEVGPVGPPGPPGPPGPPGPPSGGFDLSFLPQPPQEKAHD  1200
1201  GGRYYRADDANVMRDRDLEVDTTLKSLSQQIENIRSPEGTRKNPARTCRD  1250
1251  LKMCHGDWKSGEYWIDPNQGCNLDAIKVYCNMETGETCVYPTQATIAQKN  1300
1301  WYLSKNPKEKKHVWFGETMSDGFQFEYGGEGSNPADVAIQLTFLRLMSTE  1350
1351  ATQNVTYHCKNSVAYMDHDTGNLKKALLLQGANEIEIRAEGNSRFTYGVT  1400
1401  EDGCTSHTGAWGKTVIEYKTTKTSRLPIIDLAPMDVGAPDQEFGIDIGPV  1450
1451  CFL                                                 1453

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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