 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9TV52 from www.uniprot.org...
The NucPred score for your sequence is 0.30 (see score help below)
1 MAGGAHRADRATGEERKEGGGRWRAPHSPSPPGPRGCPVPLKAAAQSLCR 50
51 KPTWGRYCTLLLFQRKLEIYSVELHAATDIKKKEGRDGKKDNDLELKRNQ 100
101 QKEELKKELDLDDHKLSNKELETKYGTDIIRGLSSTRAAELLAQNGPNAL 150
151 TPPKQTPEIIKFLKQMVGGFSILLWVGAVLCWIAFGIQYVSNPSASLDRV 200
201 YLGTVLAVVVILTGIFAYYQEAKSTNIMASFCKMIPQQAVVIRDSEKKVI 250
251 PAEQLVVGDIVEIKGGDQIPADIRLLSAQGCKVDNSSLTGESEPQSRSSG 300
301 FTHENPLETKNITFYSTTCLEGTATGMVINTGDRTIIGRIASLASGVGNE 350
351 KTPIAIEIEHFVHIVAGVAVSVGILFFIIAVCMKYHVLDAIIFLIAIIVA 400
401 NVPEGLLATVTVALSLTAKRVAKKNCLVKNLEAVETLGSTSIICSDKTGT 450
451 LTQNRMTVAHLWFDNQIFVADTSEDNLNQGFDQSSGTWTSLSKIIALCNR 500
501 AEFKPGEESVPIMKRVVVGDASETALLKFSEVILGDVMEIRKRNHKVVEI 550
551 PFNSTNKFQLSIHQTEDPNDKRFLLVMKGAPERILEKCSTIMINGKEQPL 600
601 DKSMAQAFHTAYMELGGLGERVLGFCHFYLPADEFPETYSFDSESMNFPT 650
651 SNLCFVGLLSMIDPPRSTVPDAVTKCRSAGIKVIMVTGDHPITAKAIAKS 700
701 VGIISANSETVEDIAKRCNIAVEQVNKRDAKAAVVTGMELKDMSPEQLDE 750
751 LLANYPEIVFARTSPQQKLIIVEGCQRQDAVVAVTGDGVNDSPALKKADI 800
801 GVAMGITGSDAAKNAADMILLDDNFSSIVTGVEEGRLIFDNLKKTIAYTL 850
851 TKNIAELCPFLIYIILGLPLPIGTITLLFIDLGTDIIPSIALAYEKAESD 900
901 IMNRKPRHKKKDRLVNQQLAVYSYLHIGLMQALGAFLVYFTVYAQQGFRP 950
951 TSLFHLRIAWDSDHLNDLEDNYGQEWTSYQRQYLEWTGYTAFFVGIMVQQ 1000
1001 IADLIIRKTRKNSIFKQGLFRNKVIWVGIASQIIVALLLSYGLGSITALN 1050
1051 FTMLKAQYWFVAVPHAILIWVYDEMRKLFIRLYPGSWWDKNMYY 1094
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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