 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P55141 from www.uniprot.org...
The NucPred score for your sequence is 0.07 (see score help below)
1 MSSSRPANSSSNPGRANQNARVVLTTLDAKIHADFEESGNSFDYSSSVRV 50
51 TSAVGENSSIQSNKLTTAYLHHIQKGKLIQPVGCLLAVDEKSFKIMAYSE 100
101 NAPEMLTMVSHAVPSVGEHPVLGIGTDVRTIFTAPSAAALQKAVGFTDIN 150
151 LLNPILVHCKTSGKPFYAIAHRVTGSLIIDFEPVKPYEVPMTAAGALQSY 200
201 KLASKAVNRLQALPGGSMERLCDTMVQEVFELTGYDRVMAYKFHDDDHGE 250
251 VTAEVTKPGLEPYFGLHYPATDVPQAARFLFLKNKVRMICDCRANSAPVL 300
301 QDEKLPFELTLCGSTLRAPHSCHLQYMENMNSIASLVMAVVINDSDEVVE 350
351 SSDRNSVKSKKLWGLVVCHNTSPRFVPFPLRYACEFLAQVFAIHVSKELE 400
401 LENQIVEKNILRTQTLLCDLLMRDAPLGIVSQSPNMMDLVKCDGAALLYK 450
451 NKVYRLGATPSDYQLRDIVSWLTEYHTDSTGLSTDSLYDAGYPGALALGD 500
501 VVCGMAVVKITSHDMLFWFRSHAAGHIRWGGAKAEPDENHDGRKMHPRSS 550
551 FKAFLEVVKTRSTTWKEFEMDAIHSLQLILRKALSVEKAVAAQGDEIRSN 600
601 TDVIHTKLNDLKIEGIQELEAVTSEMVRLIETATVPIFAVDADEIVNGWN 650
651 TKIAELTGLPVDQAMGKHLLTLVEDSSVGTVVFLLALALQGKEEQGIPFE 700
701 FKTYGSREDSVPITVVVNACATRGLHDNVVGVCFVAQDVTSQKTIMDKFT 750
751 RIQGDYKAIVQNPNPLIPPIFGTDEFGWCSEWNQAMTELSGWRREDVMNK 800
801 MLLGEIFGIQTSCCHLKSKEAFVNLGVVLNNALTGQISEKICFSFFATDG 850
851 KYVECLLCASKKLHGEGTVTGIFCFLQLASQELQQALHIQRLTEQTAMKR 900
901 LKTLSYLRRQAKNPLCGINFVREKLEEIGMGEEQTKLFRTSVHCQRHVNK 950
951 ILDDTDLDSIIDGYLDLEMSEFRLHDVYVASRSQVSMRSNGKAIQVVDNF 1000
1001 SEEMMSETLYGDSLRLQKVLADFMSVCVNLTPVGGHLGISVTLTEDNLGQ 1050
1051 SVQLVHLEFRITHTGAGVPEEAVSQMFGSDSETSEEGISLLISRKLVKLM 1100
1101 NGDVHYLREAGKSTFIITVELAAASKRES 1129
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.