 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q920H8 from www.uniprot.org...
The NucPred score for your sequence is 0.12 (see score help below)
1 MKAGHLLWALLLMHSLCSLPTDGAIRNYYLGIQDIQWNYAPKGRNVITNQ 50
51 TLNNDTVASSFLKSGKNRIGGTYKKTVYKEYSDGTYTNEIAKPAWLGFLG 100
101 PLLKAEMGDVILIHLKNFASRPYTIHPHGVFYEKDSEGSLYPDGSSGYLK 150
151 ADDSVPPGGSHVYNWSIPEGHAPTEADPACLTWIYHSHVDAPRDIATGLI 200
201 GPLITCKRGTLDGNSPPQRKDVDHNFFLLFSVIDENLSWHLDDNIATYCS 250
251 DPASVDKEDGPFQDSNRMHAINGFVFGNLPELSMCAQKHVAWHLFGMGNE 300
301 IDVHTAFFHGQTLSIRGHRTDVAHIFPATFVTAEMVPQKSGTWLISCVVN 350
351 SHLKSGMQAFYKVDSCSMDPPVEQLTGKVRQYFIQAHEIQWDYGPIGHDG 400
401 RTGKSLREPGSGPDKYFQKSSSRIGGTYWKVRYEAFQDETFQERLHQEEE 450
451 THLGILGPVIRAEVGDTIQVVFYNRASQPFSIQPHGVFYEKSSEGTVYND 500
501 GTSYPKVAKSFEKVTYYWTVPPHAGPTAEDPACLTWMYFSAADPTRDTNS 550
551 GLVGPLLVCKAGALGEDGKQKGVDKEFFLLFTIFDENESWYNNANQAAGM 600
601 LDSRLLSEDVEGFEDSNRMHAINGFLFSNLPRLDICKGDTVAWHLLGLGT 650
651 ENDVHGVMFEGNTLQLQGMRKSAAMLFPHTFVTAIMQPDNPGIFEIYCQA 700
701 GSHREAGMQAIYNVSQCSSHQDSPRQHYQASRVYYIMAEEIEWDYCPDRS 750
751 WELEWYNTSEKDSYGHVFLSNKDGLLGSKYKKAVFREYTDGTFRIPQPRS 800
801 GPEEHLGILGPLIRGEVGDILTVVFKNKASRPYSIHAHGVLESSTGWPQA 850
851 AEPGEVLTYQWNIPERSGPGPSDSACVSWIYYSAVDPIKDMYSGLVGPLV 900
901 ICRNGILEPNGGRNDMDREFALLFLIFDENQSWYLKENIATYGPQETSHV 950
951 NLQDATFLESNKMHAINGKLYANLRGLTVYQGERVAWYMLAMGQDTDIHT 1000
1001 VHFHAESFLYQNGHSYRADVVDLFPGTFEVVEMVASNPGAWLMHCHVTDH 1050
1051 VHAGMETIFTVLSHEEHFSTMTTITKEIGKAVILQNIGEGNVKMLGMNIP 1100
1101 VKNVEILSSALIAICVVLLLIALALGGVVWYQHRQRKLRRNRRSILDDSF 1150
1151 KLLSLKQ 1157
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.) |
Go back to the NucPred Home Page.