 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P38570 from www.uniprot.org...
The NucPred score for your sequence is 0.52 (see score help below)
1 MWLFHTLLCIASLALLAAFNVDVARPWLTPKGGAPFVLSSLLHQDPSTNQ 50
51 TWLLVTSPRTKRTPGPLHRCSLVQDEILCHPVEHVPIPKGRHRGVTVVRS 100
101 HHGVLICIQVLVRRPHSLSSELTGTCSLLGPDLRPQAQANFFDLENLLDP 150
151 DARVDTGDCYSNKEGGGEDDVNTARQRRALEKEEEEDKEEEEDEEEEEAG 200
201 TEIAIILDGSGSIDPPDFQRAKDFISNMMRNFYEKCFECNFALVQYGGVI 250
251 QTEFDLRDSQDVMASLARVQNITQVGSVTKTASAMQHVLDSIFTSSHGSR 300
301 RKASKVMVVLTDGGIFEDPLNLTTVINSPKMQGVERFAIGVGEEFKSART 350
351 ARELNLIASDPDETHAFKVTNYMALDGLLSKLRYNIISMEGTVGDALHYQ 400
401 LAQIGFSAQILDERQVLLGAVGAFDWSGGALLYDTRSRRGRFLNQTAAAA 450
451 ADAEAAQYSYLGYAVAVLHKTCSLSYIAGAPRYKHHGAVFELQKEGREAS 500
501 FLPVLEGEQMGSYFGSELCPVDIDMDGSTDFLLVAAPFYHVHGEEGRVYV 550
551 YRLSEQDGSFSLARILSGHPGFTNARFGFAMAAMGDLSQDKLTDVAIGAP 600
601 LEGFGADDGASFGSVYIYNGHWDGLSASPSQRIRASTVAPGLQYFGMSMA 650
651 GGFDISGDGLADITVGTLGQAVVFRSRPVVRLKVSMAFTPSALPIGFNGV 700
701 VNVRLCFEISSVTTASESGLREALLNFTLDVDVGKQRRRLQCSDVRSCLG 750
751 CLREWSSGSQLCEDLLLMPTEGELCEEDCFSNASVKVSYQLQTPEGQTDH 800
801 PQPILDRYTEPFAIFQLPYEKACKNKLFCVAELQLATTVSQQELVVGLTK 850
851 ELTLNINLTNSGEDSYMTSMALNYPRNLQLKRMQKPPSPNIQCDDPQPVA 900
901 SVLIMNCRIGHPVLKRSSAHVSVVWQLEENAFPNRTADITVTVTNSNERR 950
951 SLANETHTLQFRHGFVAVLSKPSIMYVNTGQGLSHHKEFLFHVHGENLFG 1000
1001 AEYQLQICVPTKLRGLQVVAVKKLTRTQASTVCTWSQERACAYSSVQHVE 1050
1051 EWHSVSCVIASDKENVTVAAEISWDHSEELLKDVTELQILGEISFNKSLY 1100
1101 EGLNAENHRTKITVVFLKDEKYHSLPIIIKGSVGGLLVLIVILVILFKCG 1150
1151 FFKRKYQQLNLESIRKAQLKSENLLEEEN 1179
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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