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

NucPred

Fetching P12105 from www.uniprot.org...

The NucPred score for your sequence is 0.39 (see score help below)

   1  MMSFVQKVSLFILAVFQPSVILAQQDALGGCTHLGQEYADRDVWKPEPCQ    50
  51  ICVCDSGSVLCDDIICDDQELDCPNPEIPLGECCPVCPQTTPQPTELPYT   100
 101  QGPKGDPGSPGSPGRTGAPGPPGQPGSPGAPGPPGICQSCPSISGGSFSP   150
 151  QYDSYDVKAGSVGMGYPPQPISGFPGPPGPSGPPGPPGHAGPPGSNGYQG   200
 201  PPGEPGQPGPSGPPGPAGMIGPAGPPGKDGEPGRPGRNGDRGIPGLPGHK   250
 251  GHPGMPGMPGMKGARGFDGKDGAKGDSGAPGPKGEAGQPGANGSPGQPGP   300
 301  GGPTGERGRPGNPGGPGAHGKDGAPGTAGPLGPPGPPGTAGFPGSPGFKG   350
 351  EAGPPGPAGASGNPGERGEPGPQGQAGPPGPQGPPGRAGSPGGKGEMGPS   400
 401  GIPGGPGPPGGRGLPGPPGTSGNPGAKGTPGEPGKNGAKGDPGPKGERGE   450
 451  NGTPGARGPPGEEGKRGANGEPGQNGVPGTPGERGSPGFRGLPGSNGLPG   500
 501  EKGPAGERGSPGPPGPSGPAGDRGQDGGPGLPGMRGLPGIPGSPGSDGKP   550
 551  GPPGNQGEPGRSGPPGPAGPRGQPGVMGFPGPKGNEGAPGKNGERGPGGP   600
 601  PGTPGPAGKNGDVGLPGPPGPAGPAGDRGEPGPSGSPGLQGLPGGPGPAG   650
 651  ENGKPGEPGPKGDIGGPGFPGPKGENGIPGERGPQGPPGPTGARGGPGPA   700
 701  GSEGAKGPPGPPGAPGGTGLPGLQGMPGERGASGSPGPKGDKGEPGGKGA   750
 751  DGLPGARGERGNVGPIGPPGPAGPPGDKGETGPAGAPGPAGSRGGPGERG   800
 801  EQGLPGPAGFPGAPGQNGEPGGKGERGPPGLRGEAGPPGAAGPQGGPGAP   850
 851  GPPGPQGVKGERGSPGGPGAAGFPGARGPPGPPGNNGDRGESGPPGVPGP   900
 901  PGHPGPAGNNGAPGKAGERGFQGPLGPQGAIGSPGASGARGPPGPAGPPG   950
 951  KDGRGGYPGPIGPPGPRGNRGESGPAGPPGQPGLPGPSGPPGPCCGGGVA  1000
1001  SLGAGEKGPVGYGYEYRDEPKENEINLGEIMSSMKSINNQIENILSPDGS  1050
1051  RKNPARNCRDLKFCHPELKSGEYWIDPNQGCKMDAIKVYCNMETGETCLS  1100
1101  ANPATVPRKNWWTTESSGKKHVWFGESMKGGFQFSYGDPDLPEDVSEVQL  1150
1151  AFLRILSSRASQNITYHCKNSIAYMNQASGNVKKALKLMSSVETDIKAEG  1200
1201  NSKYMYAVLEDGCTKHTGEWGKTVFEYRTRKTMRLPVVDIAPIDIGGPDQ  1250
1251  EFGVDVGPVCFL                                        1262

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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