  |  Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. | 
NucPred
Fetching  Q08999  from www.uniprot.org...
The NucPred score for your sequence is 0.99 (see score help below)
   1  MPSGGDQSPPPPPPPPAAAASDEEEEDDGEAEDAAPPAESPTPQIQQRFD    50
  51  ELCSRLNMDEAARAEAWDSYRSMSESYTLEGNDLHWLACALYVACRKSVP   100
 101  TVSKGTVEGNYVSLTRILKCSEQSLIEFFNKMKKWEDMANLPPHFRERTE   150
 151  RLERNFTVSAVIFKKYEPIFQDIFKYPQEEQPRQQRGRKQRRQPCTVSEI   200
 201  FHFCWVLFIYAKGNFPMISDDLVNSYHLLLCALDLVYGNALQCSNRKELV   250
 251  NPNFKGLSEDFHAKDSKPSSDPPCIIEKLCSLHDGLVLEAKGIKEHFWKP   300
 301  YIRKLYEKKLLKGKEENLTGFLEPGNFGESFKAINKAYEEYVLSVGNLDE   350
 351  RIFLGEDAEEEIGTLSRCLNAGSGTETAERVQMKNILQQHFDKSKALRIS   400
 401  TPLTGVRYIKENSPCVTPVSTATHSLSRLHTMLTGLRNAPSEKLEQILRT   450
 451  CSRDPTQAIANRLKEMFEIYSQHFQPDEDFSNCAKEIASKHFRFAEMLYY   500
 501  KVLESVIEQEQKRLGDMDLSGILEQDAFHRSLLACCLEVVTFSYKPPGNF   550
 551  PFITEIFDVPLYHFYKVIEVFIRAEDGLCREVVKHLNQIEEQILDHLAWK   600
 601  PESPLWEKIRDNENRVPTCEEVMPPQNLERADEICIAGSPLTPRRVTEVR   650
 651  ADTGGLGRSITSPTTLYDRYSSPPASTTRRRLFVENDSPSDGGTPGRMPP   700
 701  QPLVNAVPVQNVSGETVSVTPVPGQTLVTMATATVTANNGQTVTIPVQGI   750
 751  ANENGGITFFPVQVNVGGQAQAVTGSIQPLSAQALAGSLSSQQVTGTTLQ   800
 801  VPGQVAIQQISPGGQQQKQGQSVTSSSNRPRKTSSLSLFFRKVYHLAAVR   850
 851  LRDLCAKLDISDELRKKIWTCFEFSIIQCPELMMDRHLDQLLMCAIYVMA   900
 901  KVTKEDKSFQNIMRCYRTQPQARSQVYRSVLIKGKRKRRNSGSSDSRSHQ   950
 951  NSPTELNKDRTSRDSSPVMRSSSTLPVPQPSSAPPTPTRLTGANSDMEEE  1000
1001  ERGDLIQFYNNIYIKQIKTFAMKYSQANMDAPPLSPYPFVRTGSPRRIQL  1050
1051  SQNHPVYISPHKNETMLSPREKIFYYFSNSPSKRLREINSMIRTGETPTK  1100
1101  KRGILLEDGSESPAKRICPENHSALLRRLQDVANDRGSH             1139
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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