 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P61622 from www.uniprot.org...
The NucPred score for your sequence is 0.35 (see score help below)
1 MDFPRGLLVAWTLSLWPGFTDTFNMDTRNPRVIAGPSAAFFGYTVQQHDI 50
51 SGKKWLVVGAPMETNGHQKTGDVYKCPVTQGNCTKLNLGRVTLSNVSERK 100
101 DNMRLGLSLATNPKDNSFLACSPLWSHECGSSYYTTGMCSRANSNFRFSK 150
151 TVAPALQRCQTYMDIVIVLDGSNSIYPWVEVQHFLINILKKFYIGPGQIQ 200
201 VGIVQYGEDAVHEFHLNDYRSVKDVVEAASHIEQRGGTETRTAFGIEFAR 250
251 SEAFQKGGRKGAKKVMIVITDGESHDSPDLEKVIRQSEKDNVTRYAVAVL 300
301 GYYNRRGINPETFLNEIKYIASDPDDKHFFNVTDEAALKDIVDALGDRIF 350
351 SLEGTNKNETSFGLEMSQTGFSSHVVEDGILLGAVGAYDWNGAVLKETSA 400
401 GKVIPHRESYLKEFPEELKNHAAYLGYTVTSVVSSRQGRVYVAGAPRFNH 450
451 TGKVILFSMHNNRSLTIHQALRGEQIGSYFGSEITSVDVNDDRVTDVLLV 500
501 GAPMYFSEGRERGKVYVYNLRQNRFVYNGTLKDSHSYQNARFGSCIASVQ 550
551 DLNQDSYNDVVVGAPLEDSHRGAIYIFHGFQTNILKKPMQRITASELAPG 600
601 LQHFGCSIHGQLDLNEDGLVDLAVGALGNAVVLWARPVVQINASLHFEPS 650
651 KINIFHKDCKRNGRDATCLAAFLCFIPIFLAPHFQTATVGIRYNATMDER 700
701 RYMPRAHLDEGGDQFTNRAVLLSSGQEHCQRINFHVLDTADYVKPVAFSV 750
751 EYSLEDPDNGPMLDNGWPTTLRVSVPFWNGCNEDEHCVPDLVLDARSDLP 800
801 TAMEYCQRVLGRPAQDCSSYTLSFDTTVFIIESTRRRVAVEATLENRGEN 850
851 AYSAVLNISQSENLQFASLIQKDDSDNSIECVNEERRLHKKVCNVSYPFF 900
901 RAKAKVAFRLDFEFSKSVFLHHLQIHLGAGSDSHEQDSTADDNTALLRFH 950
951 LKYEADVLFTRSSSLSHFEVKANSSLESYDGIGPPFNCVFKVQNLGFFPI 1000
1001 HGVMMKITVPIATRGGNRLLMLRDFFTDQGNTSCNIWGNSTEYRSTPTEE 1050
1051 DLSHAPQRNHSNSDVVSIICNLRLAPSQETSFYLVGNLWLTSLKALKYRS 1100
1101 LKITVNAALQRQFHSPFIFREEDPSRQVTFEISKQEDWQVPIWIIVGSTL 1150
1151 GGLLLLALLVLALWKLGFFKSAKRKREPGLGPIPKELK 1188
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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