 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q569Z2 from www.uniprot.org...
The NucPred score for your sequence is 0.75 (see score help below)
1 MADPVQSLAQLEILCKQLYETTDTSTRLQAEKALVEFTNSPECLSKCQLL 50
51 LERGSSSYSQLLAATCLTKLVSRSTNPLPLEQRIDIRNYVLTYLATRPKL 100
101 ASFVTQALIQLYARITKLGWFDSQKDDFVFRNVIGDVTRFLQDSVEYCVI 150
151 GVSFLSQLTNEINQADATHPLTKHRKIASSFRDSALFDIFTLSCNLLKQA 200
201 SGKSLLLSDESQHDLLMQLLKLTHNCLNFDFIGTSTDESSDDLCTVQIPT 250
251 SWRSAFLDSSTLQLFFDLYHSIPPNFTPLVLSCLVQIASVRRSLFNNAER 300
301 AKFLSHLVDGVKRILENPQSLSDPNNYHEFCRLLARLKSNYQLGELVKVE 350
351 NYPEVIRLIANFTVTSLQHWEFAPNSVHYLLSLWQRLAASVPYVKATEPH 400
401 LLETYTPEVTKSYVTSRLESVHIILRDGLEDPLEDAGLVQQQLDQLSTIG 450
451 RCEYDKTCALLVQLFDQSAQTYQELLQSGSAPSMELAVQEGRLTWLVYII 500
501 GAVIGGRVSFASTDEQDAMDGELVCRVLQLMNLTDSRLAQAGNEKLELSM 550
551 LSFFEQFRKIYIGDQVQKSSKLYRRLSDVLGLNDETMVLSIFIGKIITNL 600
601 KYWGRCEPITSKTLQLLNDLSIGYSSVRKLVKLSAVQFMLNNHTSEHFSF 650
651 LGINSQSNMSDMRCRTTFYTALGRLLMVDLGEDEEQFSQFMMPLTAAFES 700
701 LAQMFNSNNFNEQEAKRSLVGLVRDLRGIAFAFNAKSSFMMLFDWIYPAY 750
751 MPILQRAIELWFHDPACTTPILKLMAELVHNRSQRLQFDVSSPNGILLFR 800
801 ETSKMITTYGNRILTLGELPKEQLYVLKLKGISICFSVLKAALSGNYVNF 850
851 GVFRLYGDEALDNALQTFVKLLLSVPHSDLLDYPKLSQSYYSLLEVLTQD 900
901 HMSFIASLEPHVIMYILSSISEGLTALDTMVCTGCCSCLDHIVTYLFKQL 950
951 SRSGKKRGAPPPQESERFLHIMQQHPEMIQQMLSTVLNIIIFEDCRNQWS 1000
1001 MSRPLLGLILLNEKYFSDLRSSIVSSQPPEKQQAMHLCFENLMEGIEGNL 1050
1051 LTKNRDRFTQNLSAFRREVNDSMKNSSCGPNSNEMMS 1087
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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