 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P78611 from www.uniprot.org...
The NucPred score for your sequence is 0.75 (see score help below)
1 MSLPQRPGKTSPRREETSAFREPSRRRRRESDSLSNNDPTSPRHHRHHRS 50
51 HSSRHQHDIDEERAEEGGIRRKRSLVKPERGRMDPSHPNYLYRQKTQNMP 100
101 TYNPMTGNEPLIHEEGEAETNSTPSMDSKRKDALYGAHGNVNKPMERVPT 150
151 RHRSKKRKGSRKISKREAAAEKRRRKAMEQVRPPSLWTTYCSVITFWAPD 200
201 FVLKCFGMPQKAQRSAWREKIGLISIILMIAAFVGFLTFGFTATVCGTPP 250
251 TRLKINEIGSGYMIFHGQAYDLTKSTHPAAAGIPDMTNVLYDLPHKYGGQ 300
301 DGSFFFQEVNGACKGLITRTENSDIPTNSNGDLAWYFPCHAFNQDGSSEP 350
351 NTTVSYYNGWACHTSGSARKSFYSLKNSGDVYFTWEDTKNTSRKLAVYSG 400
401 NVLDLNLLNWFDDTQVNYPTKFKDLRDNDDIRGVDLTYYFQTGEDKQIGK 450
451 CLSQIIKVGSIDTDTVGCIASQVVLYVSLIFILSIVIVKFAFALLFQWFL 500
501 APRFAAQKTSMGAVDSKARNQQIEDWSNDIYRPGPRLADPVPGDRMSKRA 550
551 SFLPTTSRFSSPYTVSNGGKQKPQWVTMASQNSTTRLVPPASGTTPSIYR 600
601 QSHNGLGNVSVDNSRLNPSASRTSLVQDSRYSTVIPDSEGIGSAGYVHEL 650
651 VVPQPPPDWQPYGFPLAHAMCLVTCYSEGEEGIRTTLDSIALTDYPNSHK 700
701 SIVVICDGIIKGKGEEFSTPDIVLRMMRDPIIPPEEVEAFSYVAVATGSK 750
751 RHNMAKVYAGFYDYGEHSIIPVEKQQRVPMMIIVKCGTPAEATAAKPGNR 800
801 GKRDSQIILMSFLQKVMFDERMTELEYEMFNGLLHVTGIPPDFYEVVLMV 850
851 DADTKVFPDSLTHMISAMVKDPEVMGLCGETKIANKTDSWVTMIQVFEYF 900
901 VSHHQSKAFESVFGGVTCLPGCFSMYRIKAPKGGQNYWVPILANPDIVEH 950
951 YSENVVDTLHKKNLLLLGEDRYLSTLMLRTFPKRKQIFVPQAVCKTVVPD 1000
1001 KFMVLLSQRRRWINSTVHNLMELVLVRDLCGTFCFSMQFVIFVELVGTVV 1050
1051 LPAAISFTIYVVVSSIIKQPVQIIPLVLLALILGLPGVLVVVTAHRLVYV 1100
1101 LWMLVYLISLPIWNFVLPTYAYWKFDDFSWGDTRKTAGEKDKGHEDGEGE 1150
1151 FDSSKITMKRWRDFEKDRRLRMQAGWQLPVGGHPPMPYEPYPEY 1194
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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