 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9Y5S2 from www.uniprot.org...
The NucPred score for your sequence is 0.89 (see score help below)
1 MSAKVRLKKLEQLLLDGPWRNESALSVETLLDVLVCLYTECSHSALRRDK 50
51 YVAEFLEWAKPFTQLVKEMQLHREDFEIIKVIGRGAFGEVAVVKMKNTER 100
101 IYAMKILNKWEMLKRAETACFREERDVLVNGDCQWITALHYAFQDENHLY 150
151 LVMDYYVGGDLLTLLSKFEDKLPEDMARFYIGEMVLAIDSIHQLHYVHRD 200
201 IKPDNVLLDVNGHIRLADFGSCLKMNDDGTVQSSVAVGTPDYISPEILQA 250
251 MEDGMGKYGPECDWWSLGVCMYEMLYGETPFYAESLVETYGKIMNHEERF 300
301 QFPSHVTDVSEEAKDLIQRLICSRERRLGQNGIEDFKKHAFFEGLNWENI 350
351 RNLEAPYIPDVSSPSDTSNFDVDDDVLRNTEILPPGSHTGFSGLHLPFIG 400
401 FTFTTESCFSDRGSLKSIMQSNTLTKDEDVQRDLEHSLQMEAYERRIRRL 450
451 EQEKLELSRKLQESTQTVQSLHGSSRALSNSNRDKEIKKLNEEIERLKNK 500
501 IADSNRLERQLEDTVALRQEREDSTQRLRGLEKQHRVVRQEKEELHKQLV 550
551 EASERLKSQAKELKDAHQQRKLALQEFSELNERMAELRAQKQKVSRQLRD 600
601 KEEEMEVATQKVDAMRQEMRRAEKLRKELEAQLDDAVAEASKERKLREHS 650
651 ENFCKQMESELEALKVKQGGRGAGATLEHQQEISKIKSELEKKVLFYEEE 700
701 LVRREASHVLEVKNVKKEVHDSESHQLALQKEILMLKDKLEKSKRERHNE 750
751 MEEAVGTIKDKYERERAMLFDENKKLTAENEKLCSFVDKLTAQNRQLEDE 800
801 LQDLAAKKESVAHWEAQIAEIIQWVSDEKDARGYLQALASKMTEELEALR 850
851 SSSLGSRTLDPLWKVRRSQKLDMSARLELQSALEAEIRAKQLVQEELRKV 900
901 KDANLTLESKLKDSEAKNRELLEEMEILKKKMEEKFRADTGLKLPDFQDS 950
951 IFEYFNTAPLAHDLTFRTSSASEQETQAPKPEASPSMSVAASEQQEDMAR 1000
1001 PPQRPSAVPLPTTQALALAGPKPKAHQFSIKSFSSPTQCSHCTSLMVGLI 1050
1051 RQGYACEVCSFACHVSCKDGAPQVCPIPPEQSKRPLGVDVQRGIGTAYKG 1100
1101 HVKVPKPTGVKKGWQRAYAVVCDCKLFLYDLPEGKSTQPGVIASQVLDLR 1150
1151 DDEFSVSSVLASDVIHATRRDIPCIFRVTASLLGAPSKTSSLLILTENEN 1200
1201 EKRKWVGILEGLQSILHKNRLRNQVVHVPLEAYDSSLPLIKAILTAAIVD 1250
1251 ADRIAVGLEEGLYVIEVTRDVIVRAADCKKVHQIELAPREKIVILLCGRN 1300
1301 HHVHLYPWSSLDGAEGSFDIKLPETKGCQLMATATLKRNSGTCLFVAVKR 1350
1351 LILCYEIQRTKPFHRKFNEIVAPGSVQCLAVLRDRLCVGYPSGFCLLSIQ 1400
1401 GDGQPLNLVNPNDPSLAFLSQQSFDALCAVELESEEYLLCFSHMGLYVDP 1450
1451 QGRRARAQELMWPAAPVACSCSPTHVTVYSEYGVDVFDVRTMEWVQTIGL 1500
1501 RRIRPLNSEGTLNLLNCEPPRLIYFKSKFSGAVLNVPDTSDNSKKQMLRT 1550
1551 RSKRRFVFKVPEEERLQQRREMLRDPELRSKMISNPTNFNHVAHMGPGDG 1600
1601 MQVLMDLPLSAVPPSQEERPGPAPTNLARQPPSRNKPYISWPSSGGSEPS 1650
1651 VTVPLRSMSDPDQDFDKEPDSDSTKHSTPSNSSNPSGPPSPNSPHRSQLP 1700
1701 LEGLEQPACDT 1711
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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