  |  Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. | 
NucPred
Fetching  Q5SPL2  from www.uniprot.org...
The NucPred score for your sequence is 0.99 (see score help below)
   1  MWEKMETKTIVYDLDTSGGLMEQIQALLAPPKTDEAEKRSRKPEKESRRS    50
  51  GRATNHDSCDSCKEGGDLLCCDHCPAAFHLQCCNPPLSEEMLPPGEWMCH   100
 101  RCTVRRKKREQKKELGHVNGLVDKSSKRTTSPSSDTDLLDRPASKTELKA   150
 151  IAHARILERRASRPGTPTSNASTETPTSEHNDVDEDIVDVDEEPVAAEPD   200
 201  YVQPQLRRPFELLIAAAMERNPTQFQLPNELTCTTALPGSSKRRRKEETT   250
 251  GKNVKRTQHELDHNGLVPLPVKVCFTCNRSCRVAPLIQCDYCPLLFHMDC   300
 301  LEPPLTAMPLGRWMCPNHIEHVVLNQKNLTLSNRCQVFDRFQDTISQHVV   350
 351  KVDFLNRIHKKHPPNRRVLQSVKRRSLKVPDAIKSQYQFPPPLIAPAAIR   400
 401  DGELICSGVPEESQTHLLNSEHLATQAEQQEWLCSVVALQCSILKHLSAK   450
 451  QMPSPWDSEQTEKADIKPVIVTDSSITTSLQTADKAPLPSHYPLSCPSAV   500
 501  STQNSLGCSPPHQPPTLEDISCSSCVEKSKKAPCGTANGPVNTEIKANGP   550
 551  HLYSSPTDSTDPRRLPGANTPLPGLTHRQGWPRPLTPPSAGGLQNHVGII   600
 601  VKTENATGPSSCPQRSLVPVPSLPPSIPSSCASIENTSTLHRKTVQSQIG   650
 651  PSSTESRPLGSPPNATRVLTPPQAAGDSILATGANQRFCSPAPSSDGKVS   700
 701  PGTLSIGSALTVPSFPANSTAMVDLTNSLRAFMDVNGEIEINMLDEKLIK   750
 751  FLALQRVHQLFPSRVQASPGNVGTHPLASGGHHPEVQRKEVQARAVFCPL   800
 801  LGLGGAVNMCYRTLYIGTGADMDVCLTNYGHCNYVSGKHACIFYDENTKH   850
 851  YELLNYSEHGTTVDNVLYSCDFSEKTPPTPPSSIVAKVQSVIRRRRHQKQ   900
 901  DEEPSEEAAMMSSQAQGPQRRPCNCKASSSSLIGGSGAGWEGTALLHHGS   950
 951  YIKLGCLQFVFSITEFATKQPKGDASLLQDGVLAEKLSLKPHQGPVLRSN  1000
1001  SVP                                                 1003
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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