 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P38692 from www.uniprot.org...
The NucPred score for your sequence is 0.70 (see score help below)
1 MTTKPQNSKQGLAEGEMDVSSLFKRTEVIGRGKFGVVYKGYNVKTGRVYA 50
51 IKVLNLDSDSDEVEDVQREIQFLASLKQISNITRYYGSYLKDTSLWIIME 100
101 HCAGGSLRSLLRPGKIDEKYIGVIMRELLVALKCIHKDNVIHRDIKAANV 150
151 LITNEGNVKLCDFGVAAQVNQTSLRRQTMAGTPYWMAPEVIMEGVYYDTK 200
201 VDIWSLGITTYEIATGNPPYCDVEALRAMQLIIKSKPPRLEDRSYSTSLK 250
251 EFIALCLDEDPKERLSADDLLKSKFIRAHKATPTSILKELISRYLLFRDK 300
301 NKNKYKIEGSIPENEPSKPSEAPKPSQNGGGDEAQKSIASNDNEIKRVNE 350
351 GDVEMKWDFDSLSSSDYIIENNINLDALAEDNNEWATAQHDLFNYAYPDE 400
401 DSYYFDPTSHNTRPFVYQGTTIGKGYPGTIAQNSTLNAPVTNNYTNSKYP 450
451 SKMVAGTTNTSGTHTAGPMTSSKRLESKAPKQLLELFEDNEIITAENDVN 500
501 TEAPKISKSISSLNAGNSSRDDFIPSISNEVNGNINNNKMRPHLPPLSSG 550
551 NNYYSQSTPALPLLQTKFNKTSKGPPTSGLTTAPTSIEIEIPEELPNSAL 600
601 PTPASADPVLIPSTKARSSTVTAGTPSSSSSIQYKSPSNVPRRLTVSNNR 650
651 PEHCPSTITNQKLGSAVASNSGISSTPNNSNNYNNNTDSENSRGSSGSNT 700
701 ANSTQMGITNPGNVTKLSTHKASSPSRPLFGVGTSPNRKPAGSPTQNIGH 750
751 NSTHTNLAPPPTMKPMANSKDNKDILLQPLNSIPSSSTLNTISGNSSNNL 800
801 TSSNYFSNEKEGSRVNGDFKRNNPNLKLQMPLPTPVVRNKLLDPNTATSQ 850
851 NNNGMPGSAGISTNENINQFGFNTSSASNIPVSMTPISEKHIDFGGKIKR 900
901 SQSISNRKNSSASEHPLNILGSSVSGNVSGIGNNNVGSNNNSGPNNSVPL 950
951 SANTGNTTIKANSTTIATSSSAAASTTAPISQQTIPSGTQFNHILSSAAT 1000
1001 AANSVNSLGFGMCPPPQSLQMEMFLDLESFLPGKQRRVDRKPQVLKELEN 1050
1051 LLQMFEEGLPCIEHALKEQLISTPIKDNEH 1080
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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