 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q6NRY2 from www.uniprot.org...
The NucPred score for your sequence is 0.79 (see score help below)
1 MQKKRSRAGAAEQEAASDDGEMSDSSDKMEVSQNKGKSGIKRAPEADDVL 50
51 RPVKLSKSDLYKPPTNDELNRLKETENLFHTNLLRMQIEELLQEVKLKEK 100
101 RRKTIDGFLHEINALLGTIPETPKTDLTDQSWLSSSIKVPFLQVPYQVKG 150
151 KFSFLPPSSIKVVGSYLLGTCIKPEINVDLAVTMPQEILQVKDNLNQRYS 200
201 RKRALYLAHIASHLTDNKLFSSVKFTYMNSNHLKPILLLRPQGKDEKLVT 250
251 VRIHICPPPGFFKLSRLYPNKNNVRTSWYTEQQTETEGVCDPPTPYYNNT 300
301 ILSDLTLEHHLHHLTNCATDFPGMKDAIALLKVWLHQRQLDKGFGCFNGF 350
351 LASMLISYLLSKNKINKVMSGYQVLRNTLQFLATTDLTVNGITMATCSDS 400
401 SLPSLPDFHEAFQVVFVDPMGVVNLCADMTASKYRQIQFEASESLKVLDD 450
451 TNVNGFHLLLMVPKPFVRTFDHVFHLTNVAKLQGTCKKMKLLNQLIDRGG 500
501 DYLATALPYLLSVLSKGLGPRVSLLSHTLTHKPEWNVGEEPAKHKDSGLV 550
551 TVGLLLDPELYTNVLDKGPAADSSEALDFRAFWGEKSELRRFQDGSICEA 600
601 VVWTGGSLYDKRKVPELIVKYLLELHANIPESCINYTGNALDCVLSRGRE 650
651 TSTEEEKMVSIIQSYDDLSRKLWNLNDLPLTITSVQGTHPCLRYTDVFPP 700
701 LPVKPDWSSYHLLREKKCLIPNPEKPCPAYVSPVKVICHMEGSGKWPQDK 750
751 DAIKRLKAAFQIRLSELLSSQHQLLCNPSATHTDVYKDGYVFRVQVAYHR 800
801 EPQYMKEFVTPEGMLKYQDTEESMQLEMETNHLPHLSSTLHGLHQQHPAF 850
851 GGTSRLAKRWIQSQLLGDSFSEECLDLLVAHLFLHPAPYSPPSSALVGFL 900
901 RFLHLVATFDWKNSPLIVNLNGELKGSEYTEIQNDFISARAQLPVMFIAT 950
951 PKDKKDSVWTKNQPTAQMLQRLIVLCLESLRALEQQLMDPRGNHDYKMIF 1000
1001 RPPLDLYDVLIRLNPKQISRHREAVDQPAKSFFRGMLKEGAQVKDLMFPV 1050
1051 VGYDPIQLFLQELREAYGEFALFFHDLHGGDVIGVLWKPSSFEPQPFKTT 1100
1101 NVKGRQMDGKSDKALLVPNAEAFVEDLEILGEGLVAGVEAQTERWNI 1147
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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