  |  Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. | 
NucPred
Fetching  O94988  from www.uniprot.org...
The NucPred score for your sequence is 0.98 (see score help below)
   1  MGAGALAICQSKAAVRLKEDMKKIVAVPLNEQKDFTYQKLFGVSLQELER    50
  51  QGLTENGIPAVVWNIVEYLTQHGLTQEGLFRVNGNVKVVEQLRLKFESGV   100
 101  PVELGKDGDVCSAASLLKLFLRELPDSLITSALQPRFIQLFQDGRNDVQE   150
 151  SSLRDLIKELPDTHYCLLKYLCQFLTKVAKHHVQNRMNVHNLATVFGPNC   200
 201  FHVPPGLEGMKEQDLCNKIMAKILENYNTLFEVEYTENDHLRCENLARLI   250
 251  IVKEVYYKNSLPILLTRGLERDMPKPPPKTKIPKSRSEGSIQAHRVLQPE   300
 301  LSDGIPQLSLRLSYRKACLEDMNSAEGAISAKLVPSSQEDERPLSPFYLS   350
 351  AHVPQVSNVSATGELLERTIRSAVEQHLFDVNNSGGQSSEDSESGTLSAS   400
 401  SATSARQRRRQSKEQDEVRHGRDKGLINKENTPSGFNHLDDCILNTQEVE   450
 451  KVHKNTFGCAGERSKPKRQKSSTKLSELHDNQDGLVNMESLNSTRSHERT   500
 501  GPDDFEWMSDERKGNEKDGGHTQHFESPTMKIQEHPSLSDTKQQRNQDAG   550
 551  DQEESFVSEVPQSDLTALCDEKNWEEPIPAFSSWQRENSDSDEAHLSPQA   600
 601  GRLIRQLLDEDSDPMLSPRFYAYGQSRQYLDDTEVPPSPPNSHSFMRRRS   650
 651  SSLGSYDDEQEDLTPAQLTRRIQSLKKKIRKFEDRFEEEKKYRPSHSDKA   700
 701  ANPEVLKWTNDLAKFRRQLKESKLKISEEDLTPRMRQRSNTLPKSFGSQL   750
 751  EKEDEKKQELVDKAIKPSVEATLESIQRKLQEKRAESSRPEDIKDMTKDQ   800
 801  IANEKVALQKALLYYESIHGRPVTKNERQVMKPLYDRYRLVKQILSRANT   850
 851  IPIIGSPSSKRRSPLLQPIIEGETASFFKEIKEEEEGSEDDSNVKPDFMV   900
 901  TLKTDFSARCFLDQFEDDADGFISPMDDKIPSKCSQDTGLSNLHAASIPE   950
 951  LLEHLQEMREEKKRIRKKLRDFEDNFFRQNGRNVQKEDRTPMAEEYSEYK  1000
1001  HIKAKLRLLEVLISKRDTDSKSM                             1023
Positively and negatively influencing subsequences are coloured according to the following scale:
(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)
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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