 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q04217 from www.uniprot.org...
The NucPred score for your sequence is 0.89 (see score help below)
1 MGTYRKRFNEKARSGHMAKLKELKRIRNKQFTRQDENDERVENPDSAPAE 50
51 SSTTEPNANAEILEPLTEEEKKMKKRKLQELFTPKESKVSRLKKKRLDKF 100
101 IEHQLKREERKTIIGKLQDYKIDTSLLTSSKRLGEGRQTKKEEFKEALSL 150
151 ERQGRGNEQTNEILYEEYEPKVWDEYGEGGSSEDDDGEDDFEASFGSMPK 200
201 PTDNEEKKSSGFIDHRPAKFGGSGLSFGFSNIKVINKESKTPKKKYNWRQ 250
251 RVEMEELKKHGKEDEMDFDTTSEDDDEEEDQEEEDKMHPSENPLEEVESA 300
301 DSETGSEKFDQNDVANEFKDWANQEIKKLEGRDQELVTPTLNIDYKPIIR 350
351 KEDLDDGLQEAYVPINENSTRKAFYVEVSRSDEIQKARIQLPVFGEEHKI 400
401 MEAIHHNDVVIICGETGSGKTTQVPQFLYEAGFGAEDSPDYPGMVGITQP 450
451 RRVAAVSMAERVANELGDHGHKVGYQIRFDSTAKEDTKVKFMTDGVLLRE 500
501 MMHDFKLTKYSSIIIDEAHERNINTDILIGMLSRCVRLRAKLHKENPIEH 550
551 KKLKLIIMSATLRVSDFSENKTLFPIAPPVLQVDARQFPVSIHFNRRTAF 600
601 NYTDEAFRKTCKIHQKLPPGAILVFLTGQQEITHMVKRLRKEFPFKKNSK 650
651 YNKDLETPVSKMGINSKTTDLEAEDIDFSVQVIDQDKFKSAIRYEEDEGN 700
701 SGNGEDEEDEEEEGFEEVLTEGQTANDPLYVLPLYSLLPTKEQMRVFQKP 750
751 PQGSRLCIVATNVAETSLTIPGVRYVVDSGRSKERKYNESNGVQSFEVGW 800
801 VSKASANQRSGRAGRTGPGHCYRLYSSAVFEHDFEQFSKPEILRMPVESI 850
851 VLQMKSMAIHNIINFPFPTPPDRVALSKAIQLLQYLGALDNKEMITEDGK 900
901 KMSLFPLSPRFSKMLLVSDEKACLPYIVAIVSALSVGDPFINEFELGINE 950
951 ISRKPNPDENLDDKIREHDESTPGMDPELKKELRSKFYKSRSQFSKLDKF 1000
1001 SDVFRLLSVVSAMDYVPKEQKEIFMKKNFLRGKLMEEIVKLRKQLMYIIK 1050
1051 SNTSKENIAVVIRNEDLKSDIPSVIQIKLLKQMICAGFVDHVAVRADVLF 1100
1101 PDDAKITNRTSIINIPYIPVLATRTPNIEDCFVYIHPTSILNNLGEMPPK 1150
1151 YMLYYSLHLGGNNKTRMNTLCDIASTPLANIARKGLLLTYSKPLTGQGLK 1200
1201 TVNLSPTERYCYVVPRFGSTVDNDLKIGWDLNPIAVHQKKQKGQWTVIKF 1250
1251 ITRKGFQTITGEEKEKK 1267
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.