 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8TEX9 from www.uniprot.org...
The NucPred score for your sequence is 0.52 (see score help below)
1 MESAGLEQLLRELLLPDTERIRRATEQLQIVLRAPAALPALCDLLASAAD 50
51 PQIRQFAAVLTRRRLNTRWRRLAAEQRESLKSLILTALQRETEHCVSLSL 100
101 AQLSATIFRKEGLEAWPQLLQLLQHSTHSPHSPEREMGLLLLSVVVTSRP 150
151 EAFQPHHRELLRLLNETLGEVGSPGLLFYSLRTLTTMAPYLSTEDVPLAR 200
201 MLVPKLIMAMQTLIPIDEAKACEALEALDELLESEVPVITPYLSEVLTFC 250
251 LEVARNVALGNAIRIRILCCLTFLVKVKSKALLKNRLLPPLLHTLFPIVA 300
301 AEPPPGQLDPEDQDSEEEELEIELMGETPKHFAVQVVDMLALHLPPEKLC 350
351 PQLMPMLEEALRSESPYQRKAGLLVLAVLSDGAGDHIRQRLLPPLLQIVC 400
401 KGLEDPSQVVRNAALFALGQFSENLQPHISSYSREVMPLLLAYLKSVPLG 450
451 HTHHLAKACYALENFVENLGPKVQPYLPELMECMLQLLRNPSSPRAKELA 500
501 VSALGAIATAAQASLLPYFPAIMEHLREFLLTGREDLQPVQIQSLETLGV 550
551 LARAVGEPMRPLAEECCQLGLGLCDQVDDPDLRRCTYSLFAALSGLMGEG 600
601 LAPHLEQITTLMLLSLRSTEGIVPQYDGSSSFLLFDDESDGEEEEELMDE 650
651 DVEEEDDSEISGYSVENAFFDEKEDTCAAVGEISVNTSVAFLPYMESVFE 700
701 EVFKLLECPHLNVRKAAHEALGQFCCALHKACQSCPSEPNTAALQAALAR 750
751 VVPSYMQAVNRERERQVVMAVLEALTGVLRSCGTLTLKPPGRLAELCGVL 800
801 KAVLQRKTACQDTDEEEEEEDDDQAEYDAMLLEHAGEAIPALAAAAGGDS 850
851 FAPFFAGFLPLLVCKTKQGCTVAEKSFAVGTLAETIQGLGAASAQFVSRL 900
901 LPVLLSTAQEADPEVRSNAIFGMGVLAEHGGHPAQEHFPKLLGLLFPLLA 950
951 RERHDRVRDNICGALARLLMASPTRKPEPQVLAALLHALPLKEDLEEWVT 1000
1001 IGRLFSFLYQSSPDQVIDVAPELLRICSLILADNKIPPDTKAALLLLLTF 1050
1051 LAKQHTDSFQAALGSLPVDKAQELQAVLGLS 1081
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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