 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q7TT49 from www.uniprot.org...
The NucPred score for your sequence is 0.94 (see score help below)
1 MSAKVRLKKLEQLLLDGPWRNESSLSVETLLDVLVCLYTECSHSALRRDK 50
51 YVAEFLEWAKPFTQLVKDMQLHREDFEIIKVIGRGAFGEVAVVKMKNTER 100
101 IYAMKILNKWEMLKRAETACFREERDVLVNGDCQWITALHYAFQDENYLY 150
151 LVMDYYVGGDLLTLLSKFEDKLPEDMARFYIGEMVLAIDSIHQLHYVHRD 200
201 IKPDNVLLDVNGHIRLADFGSCLKMNDDGTVQSSVAVGTPDYISPEILQA 250
251 MEDGMGKYGPECDWWSLGVCMYEMLYGETPFYAESLVETYGKIMNHEERF 300
301 QFPSHVTDVSEEAKDLIQRLICSRERRLGQNGIEDFKKHAFFEGLNWENI 350
351 RNLEAPYIPDVSSPSDTSNFDVDDDVLRNIEILPPGSHTGFSGLHLPFIG 400
401 FTFTTESCFSDRGSLKSMIQSNTLTKDEDVQRDLENSLQIEAYERRIRRL 450
451 EQEKLELSRKLQESTQTVQSLHGSTRALGNSNRDKEIKRLNEELERMKSK 500
501 MADSNRLERQLEDTVTLRQEHEDSTQRLKGLEKQYRLARQEKEELHKQLV 550
551 EASERLKSQTKELKDAHQQRKRALQEFSELNERMAELRSQKQKVSRQLRD 600
601 KEEEMEVAMQKIDSMRQDIRKSEKSRKELEARLEDAVAEASKERKLREHS 650
651 ESFSKQMERELETLKVKQGGRGPGATLEHQQEISKIRSELEKKVLFYEEE 700
701 LVRREASHVLEVKNVKKEVHESESHQLALQKEVLMLKDKLEKSKRERHSE 750
751 MEEAIGAMKDKYERERAMLFDENKKLTAENEKLCSFVDKLTAQNRQLEDE 800
801 LQDLASKKESVAHWEAQIAEIIQWVSDEKDARGYLQALASKMTEELETLR 850
851 SSSLGSRTLDPLWKVRRSQKLDMSARLELQSALEAEIRAKQLVHEELRKV 900
901 KDTSLAFESKLKESEAKNRELLEEMQSLKKRMEEKFRADTGLKLPDFQDP 950
951 IFEYFNTAPLAHDLTFRTSSASDQETQASKLDLSPSVSVATSTEQQEDAA 1000
1001 RSQQRPSTVPLPNTQALAMAGPKPKAHQFSIKSFPSPTQCSHCTSLMVGL 1050
1051 IRQGYACEVCAFSCHVSCKDSAPQVCPIPPEQSKRPLGVDVQRGIGTAYK 1100
1101 GYVKVPKPTGVKKGWQRAYAVVCDCKLFLYDLPEGKSTQPGVIASQVLDL 1150
1151 RDDEFAVSSVLASDVIHATRRDIPCIFRVTASLLGSPSKTSSLLILTENE 1200
1201 NEKRKWVGILEGLQAILHKNRLRSQVVHVAQEAYDSSLPLIKTVLAAAIV 1250
1251 DGDRIAVGLEEGLYVIELTRDVIVRAADCKKVYQIELAPKEKLILLLCGR 1300
1301 NHHVHLYPWTSFDGAEASNFDIKLPETKGCQLIATGTLRKSSSTCLFVAV 1350
1351 KRLVLCYEIQRTKPFHRKFNEIVAPGHVQWMAMFKDRLCVGYPSGFSLLS 1400
1401 IQGDGQPLDLVNPADPSLAFLSQQSFDALCAVELKSEEYLLCFSHMGLYV 1450
1451 DPQGRRSRTQELMWPAAPVACSCSSSHVTVYSEYGVDVFDVRTMEWVQTI 1500
1501 GLRRIRPLNSDGSLNLLGCEPPRLIYFKNKFSGTVLNVPDTSDNSKKQML 1550
1551 RTRSKRRFVFKVPEEERLQQRREMLRDPELRSKMISNPTNFNHVAHMGPG 1600
1601 DGMQVLMDLPLSAAPTAQEEKQGPAPTGLPRQLPSRNKPYVSWPSSGGSE 1650
1651 PGVPVPLRSMSDPDQDFDKEPDSDSTKHSTPSNSSNPSGPPSPNSPHRSQ 1700
1701 LPLEGLDQPACDA 1713
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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