 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P90829 from www.uniprot.org...
The NucPred score for your sequence is 0.51 (see score help below)
1 MTSKRPGGSSFQPEVKRKRESDEFEQCYVSRFENELPSVPTIDKTGWARP 50
51 AVDKDLGISKSIACQILEVETYHEDGSATSYDRTNVKLYGVTKSGNSICV 100
101 IVTDYFPHFYFQAPQGFGVEHIGTAQSAICNMVAAAKRRGGSGQAQLPGK 150
151 VVDNLVHVEIVHGENLYYFRGADTKVPFVKVSGSTEALHKARMELKNGVN 200
201 LMGKGPVNVGNLYESNINVIVMFLAKTNIVGCGWIEIPAGKCRILSNSEK 250
251 SSRCQIEVTVPVKNLIVHESDGEWAGIAPIRTLSLDIECIGRRGVFPEAI 300
301 KDPIIQIANLVKIEGEAEPFVRNCFVLGTCAPVVGSNIIQCVNEKVLLEK 350
351 WAEFVREVDPDIITGYNILNFDLPYILDRAKVLSLPQVSHLGRQKEKGSV 400
401 VRDAAISSKQMGSRVNKSIDIHGRIIFDVLQVVLRDYKLRSYTLNSVSYQ 450
451 FLSEQKEDVEHNIIPDLQRGDEQTRRRLAQYCLKDAYLPLRLLDKLMSII 500
501 NYIEMARVTGVPMNFLLTKGQQIKILSMMLRRCKQNNFFLPVIEANSGDG 550
551 EGYEGATVIDPIRGFYNEPIATLDFASLYPSIMIAHNLCYTTLLKSPQGV 600
601 ENEDYIRTPSGQYFATKSKRRGLLPEILEDILAARKRAKNDMKNEKDEFK 650
651 RMVYNGRQLALKISANSVYGFTGATVGKLPCLEISQSVTAFGRKMIDMTK 700
701 LEVERIYKKGALDGKCPADAKVIYGDTDSVMVKFGVETVAQAMEIGLDAA 750
751 KEVSKIFTPPIKLEFEKVYSPYLLINKKRYAGLYFTKPDVHDKMDCKGLE 800
801 TVRRDNCPLVAKVLGVCLEKLLIERDQQSALDFAKRTISDLLCNKIDISL 850
851 LIISKELTKSGDKYQAKQAHVELAARMKKRDAGSAPRLGDRVPYVFVAAA 900
901 KNVPAYERAEDPTFVLQNNIPLDTKHYLTNQLAKPLARIFEPILGDRAEK 950
951 ILVEGEHTRVRTVVQSKVGGLAAFTTKSATCLGCKSVLPRAESENAVCKH 1000
1001 CEPKLPTIFASRMNTMHELENHFGRLWTECQNCAKTMQDKVNCSARDCPI 1050
1051 YYMREKVRNELSEASAVIERFGDPCFQAPTK 1081
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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