 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9UUE1 from www.uniprot.org...
The NucPred score for your sequence is 0.28 (see score help below)
1 MTSKYDALLHNQSTNTNPFSKLQDRSSLLGEKFTKVLVANRSEIAIRVFR 50
51 TAHELSMHTVAIYSYEDRLSMHRQKADESYPIGKVGQYSPVGAYLAIDEI 100
101 VSIAKRTGANLVHPGYGFLSENAEFARKVNEAGMQFVGPSPEVIDSLGDK 150
151 TKARAIAIRCGVPVVPGTPGPVEHYEEAEAFVKEYGLPVIIKAAMGGGGR 200
201 GMRVVRSADTLKESFERARSEALASFGDGTVFIERFLDKPKHIEIQLMAD 250
251 KAGNVIHLHERDCSVQRRHQKVVEIAPAKDLDPKIRQALYDDAIKIAKEV 300
301 KYCNAGTAEFLLDQKGRHYFIEINPRIQVEHTITEEITGVDIVSAQLHVA 350
351 AGFTLPEIGLTQDKISTRGFAIQCRVTTEDPNNGFAPDIGKIEVYRSAGG 400
401 NGVRLDGANGFAGSVITPHYDSMLVKCTCHDATYEYTRRKMIRSLIEFRV 450
451 RGVKTNIPFVLRLLMHDTFIQGNCWTTFIDDTPELFQLYRSRNRAQKLLA 500
501 YLGDLAVNGSSIKGQNGEPALKSEIVMPVLLDSTGNQIDVSHPSEKGWRK 550
551 LLLDNGPAAFAKAVRNHKRGLIMDTTWRDAHQSLLATRVRTIDLVNIAPY 600
601 TSHALASAYSLEMWGGATFDVSMRFLHECPWDRLRRLRKLVPNIPFQMLL 650
651 RGANGLCYSSLPDNVIYFFCEQAKKNGIDIFRVFDALNDVNNLSLGIDAA 700
701 KRAGGVVEATMCYSGDMLNPKKKYNLDYYVNLVDKMVEMGIHILGIKDMA 750
751 GVMKPKAARLLISAIREKHPELPIHVHTHDSAGTAVASMAAALEAGADVV 800
801 DVATDSMSGLTSQPSFGAVLASVDGTDKQLEFDNNQLREIDSYWAQMRLL 850
851 YSPFESEIKGTDSDVYNHEIPGGQLTNLKFQATSLGLGTQWAETKKAYIE 900
901 ANKLLGDIIKVTPTSKVVGDLAQFMVQNKLSAEDVENRATTLDFPASVLD 950
951 FFQGLMGQPYGGFPEPLRTNVLKGRRQPLTDRPGKFLPAADFDAIRKLLS 1000
1001 EKFGVSSDCDIAAYTQFPGVFEEYRQFVDRYGDLTTVPTKFFLSRPEMNE 1050
1051 EMHVEIDQGKTLIVKFVALGPLNPRTGQREVYFELNGENRHVTVEDKKAA 1100
1101 IETVTRPRADPGNPGHVAAPMSGTIVEIRVKEGAKVKKGDIIAVLSAMKM 1150
1151 EIVISAPHSGVLKSLAVVQGDSVNGGDLCAVLEHE 1185
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.) |
Go back to the NucPred Home Page.