  |  Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. | 
NucPred
Fetching  Q7Z3B3  from www.uniprot.org...
The NucPred score for your sequence is 0.99 (see score help below)
   1  MAAMAPALTDAAAEAHHIRFKLAPPSSTLSPGSAENNGNANILIAANGTK    50
  51  RKAIAAEDPSLDFRNNPTKEDLGKLQPLVASYLCSDVTSVPSKESLKLQG   100
 101  VFSKQTVLKSHPLLSQSYELRAELLGRQPVLEFSLENLRTMNTSGQTALP   150
 151  QAPVNGLAKKLTKSSTHSDHDNSTSLNGGKRALTSSALHGGEMGGSESGD   200
 201  LKGGMTNCTLPHRSLDVEHTTLYSNNSTANKSSVNSMEQPALQGSSRLSP   250
 251  GTDSSSNLGGVKLEGKKSPLSSILFSALDSDTRITALLRRQADIESRARR   300
 301  LQKRLQVVQAKQVERHIQHQLGGFLEKTLSKLPNLESLRPRSQLMLTRKA   350
 351  EAALRKAASETTTSEGLSNFLKSNSISEELERFTASGIANLRCSEQAFDS   400
 401  DVTDSSSGGESDIEEEELTRADPEQRHVPLRRRSEWKWAADRAAIVSRWN   450
 451  WLQAHVSDLEYRIRQQTDIYKQIRANKGLIVLGEVPPPEHTTDLFLPLSS   500
 501  EVKTDHGTDKLIESVSQPLENHGAPIIGHISESLSTKSCGALRPVNGVIN   550
 551  TLQPVLADHIPGDSSDAEEQLHKKQRLNLVSSSSDGTCVAARTRPVLSCK   600
 601  KRRLVRPNSIVPLSKKVHRNSTIRPGCDVNPSCALCGSGSINTMPPEIHY   650
 651  EAPLLERLSQLDSCVHPVLAFPDDVPTSLHFQSMLKSQWQNKPFDKIKPP   700
 701  KKLSLKHRAPMPGSLPDSARKDRHKLVSSFLTTAKLSHHQTRPDRTHRQH   750
 751  LDDVGAVPMVERVTAPKAERLLNPPPPVHDPNHSKMRLRDHSSERSEVLK   800
 801  HHTDMSSSSYLAATHHPPHSPLVRQLSTSSDSPAPASSSSQVTASTSQQP   850
 851  VRRRRGESSFDINNIVIPMSVAATTRVEKLQYKEILTPSWREVDLQSLKG   900
 901  SPDEENEEIEDLSDAAFAALHAKCEEMERARWLWTTSVPPQRRGSRSYRS   950
 951  SDGRTTPQLGSANPSTPQPASPDVSSSHSLSEYSHGQSPRSPISPELHSA  1000
1001  PLTPVARDTPRHLASEDTRCSTPELGLDEQSVQPWERRTFPLAHSPQAEC  1050
1051  EDQLDAQERAARCTRRTSGSKTGRETEAAPTSPPIVPLKSRHLVAAATAQ  1100
1101  RPTHR                                               1105
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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