 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P55004 from www.uniprot.org...
The NucPred score for your sequence is 0.21 (see score help below)
1 MENYGKAVTFSSSATSNLNTGKAIAQYNADAKLMAEFEQSRESGKSFDYS 50
51 RSVIHAPQNVTEEEMTAYLSRIQRGGLIQPFGCMLAIEEPSFKIVGFSEN 100
101 CFDLLGLKSGVEPPERMSLIGIDARTLFTLSSRASLAKAVASREISLLNP 150
151 IWVHSKINQKPFYAVLHRIDVGIVIDLEPANSADPALLLAGAVQSQKLAV 200
201 RAISRLQSLPGGDIGTLCDTVVEDVQKLTGYDRVMVYKFHDDSHGEVVSE 250
251 IRRSDLEPYLGLHYPATDIPQAARFLFKQNRVRMICDCNAQPVKVLQCEE 300
301 LKQPLCLVNSTLRSPHGCHTKYMANMGSIASLVMAVVINSSESMKLWGLV 350
351 VCHHTSPRYVPFPLRYACEFLMQAFSLQLYMELQLASQLAEKKILQTQTL 400
401 LCDMLLRDAPFGIVTQTPSIMDLVRCDGAALYYNGKCWLLGVTPTETQVK 450
451 DIAEWLLHNHGDSTGLSTDCLSDAGYPGAPLLGDAVSGMATARITSKDFL 500
501 FWFRSHTAKEVKWGGAKHHPEDKDDGGRMHPRSSFIAFLEVVKSRSLPWE 550
551 DSEINAIHSLQLIMRDSLQGIGENYMKSVSSPQQNDSDGVRFYELSSMAL 600
601 ELVRLVETATVPIFGVDSSGLINGWNAKIAELTGLQANVAIGKYLIDDVT 650
651 HEDSHETFKALMCRALQGEEDRNVEVKLLKFGNHPTKEVVYLVVNACTSR 700
701 DYKNDIIGVCFVGQDITPEKAVMDKFVRLQGDYEAIIQSLNPLIPPIFAS 750
751 DENACCSEWNAAMERLTGLVKCEVIGKRLPGEIFGGLCRLKGQDALTKFM 800
801 ILLYQGISGHDTEKLSFGFFDRKGNFIDVFITANKRTDERGNIIGCFCFL 850
851 QTMAVDHPQISARDIEDDRECLSTLKEFAYIQQQMKNPLNGIRFTHKLLE 900
901 GTVTSDHQKQFLETSEACEKQILSIIENMDSGGIVDGNRVELKTEEFVIG 950
951 NVIDAVVSQVMIPLKEKNLQLLHDIPDQIKSLPIYGDQIKLQLVLSDFLL 1000
1001 SIVRHAPSPDGWVEIRVSPGLKLIQDGNVFIHIQFRMTHPGQGLPSALIE 1050
1051 DMVRGGTRWTTQEGVVLHLSQKLVRMMNGHVHYVREQQKCYFLIDLDFKT 1100
1101 QKPRSRESSMDTKAD 1115
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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