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

NucPred

Fetching O74304 from www.uniprot.org...

The NucPred score for your sequence is 0.81 (see score help below)

   1  MENILDPSVVNSHILENGSRRSSINPILDSELRDKTFEKAHRRSLTLLSS    50
  51  FTSSMLELPNNGKEENHRRPSVARSSSDRSKASAKEDLFSEAFRMAEQPP   100
 101  AEALTISTPVDPINIDELDRAYAVSPSDTSNLLHPPTSSSSIPIPIKNAG   150
 151  HSNLDHPIRPSLQSSISSNRIIKSPGIKEDDYMHRGRSISSPMIDVEHIN   200
 201  STAVPSKTKNLPEKPKRSHKLRNSITFAKIEDHPERKSQLRRLSSSLKCF   250
 251  DPEYDYNDPSLSIRRDSSTYYFSNVNETYDEEDSDLDSETSTVNWVQSVL   300
 301  NLPSLLSDDLMANPKNKERFEWQYMLTSVLTGDIVRSEKLRLRKIASSRE   350
 351  GRNSDYSDNLWMEIWCWLTHRSVDSYRENLKHLRTGMVDVLLAIMNFHWD   400
 401  ESNELTPIVAVDNMLQKLDKYERLYPSRRSILQEHSLYASESFQHKLDVL   450
 451  TAYSNVTHALEIQVNIIRSWVGNEEMDITKNTTNSINNVSQISNGPFVER   500
 501  FYRETGLIRAFEQRIMTNMNSVLSKVCNTIVTYADDLKSYGLPLIADDYM   550
 551  RLLSFPFRLIKEFLNLRLSCAENITSISLFTIDSLLDDLRNTMKVAVHII   600
 601  QQHTVLIKPFRDDSKFVDENQSLNNILVASLKFYFNLLHRKVRNGCALLH   650
 651  FKETEILEGEWDFLLAVCPHIEHGFQIMSKSLSSLVGEILTNINRYLKDQ   700
 701  LQGPDTDDSALITSFYIKVLDCVRIRFRKLMSFTRILKAHLENSCEYVIK   750
 751  ENSLSLLIQRLEESNHVLTYTASIEHEGAYVIVPGHLVDSPNILREVLSM   800
 801  TFNKGDNNFESVPPYAVVLAPDSSICWNGHVTDLDIPEVSISIAPNCVRL   850
 851  VTLATANQLSVIEDYFISIVGDTVSLVDSAKANSSKINKQMTKIKRNSLK   900
 901  LALSLLDVIQTIRTRYHGMNCQNLIHYSFSYAIEFAQRLMRLSILDASSI   950
 951  GLIRRKMIQLAISWVGFIYEDCSPTDRNTFRWTVTALEFAMIMTYGSNIL  1000
1001  MIDKKSFEELKEKVGKCVALLLLHFDVMGTKHAGRSMDQQAGDIPARLVR  1050
1051  NNSDRSRLSDNELASFVKEEVMHRIIELESNRRDRLYKSQLIGRVLDDTT  1100
1101  KENRLLKELASSKSNITIRWQQGGLIGSGSFGTVYRAVNLDTGDLMAVKE  1150
1151  VALHKPRISRPMIKRIKGEMLVLELFDHPNVVSYYGIEVHREKVNIFMEL  1200
1201  CQGSSLFEFLRYGRIEDELVIQVYVLQLLEGLAYIHSCGVSHQDVKPENI  1250
1251  LFDHNGIMKFTDFGSAKMSGSASTKIFEQLTQQEEEEFEKDSEFLQHLDQ  1300
1301  NRGYSLTGTPTYMAPELILGNPSERVGAMDIWSLGCVIVEMATGSPPWPR  1350
1351  LDNHFSLMYHIAAHNPPIIPADDQLSPLGQNFLKRCFVSDPNQRATAAEL  1400
1401  LMDPWVYPLRAGTEFDLMNSSVVESAPSTNGAPLEL                1436

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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