 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q06321 from www.uniprot.org...
The NucPred score for your sequence is 0.69 (see score help below)
1 MPITQIISASDSEAGPKPSISLVPDKPSEPETSPRHHRLSRSLSKFKRWR 50
51 GRSNSSLSMGSSEQQELQDSPNEARSDDDENGYNNDNADDLAKSKYMMKS 100
101 IAGLLTTASVYAGMNNAQEMNVLSQVDSEESDSSDSFQENIGRNEVKSKK 150
151 ENLKTKSHPEVPRLDKRKPTLFDFSITREKLSKDNVAKLRQRFCLDEQEP 200
201 FLNDFPAWLLKDVLVQGHIFITTKHFLFFAYLPKNPRSVKMSGNLNIRTK 250
251 LIRSTRYWCVLKNHLFSMYTSSTELYFPVLTIDLREVQKIETQKHTLNGS 300
301 ATKTFKLYTDESTFKFNADSEFSAKSWVNALKKEQFAAQNSENNSISLKI 350
351 PLPNIIEIDDQPIVNKALTLRLRALESSQTYAIDDFMFVFMDGSGSQVKE 400
401 SLGEQLAILQKSGVNTLYYDIPAKKSKSSFGKETPATVEQKNNGEDSKYL 450
451 NVPTSAVPSSENGKKSRFRFRERSNSWFRRAKPLEDSQVEDVEEIYKDAA 500
501 NDIDSSVHSTIHIHEQEDSQEQTVAWKPSHLKNFAEMWAAKPIHYRNKFI 550
551 PFQKDDTYLIKETEEVSANERFRYHFKFNKEKSLISTYYTYLNRNVPVYG 600
601 KIYVSNDTVCFRSLLPGSNTYMVLPLVDVETCYKEKGFRFGYFVLVIVIH 650
651 GHEELFFEFSTEVARDDIERILLKLLDNIYASSAEGSNISSASLGDVQHN 700
701 PDSAKLKLFEDKINAEGFEVPLMIDENPHYKTSIKPNKSYKFGLLTIGSR 750
751 GDVQPYIALGKGLIKEGHQVVIITHSEFRDFVESHGIQFEEIAGNPVELM 800
801 SLMVENESMNVKMLREASSKFRGWIDALLQTSWEVCNRRKFDILIESPSA 850
851 MVGIHITEALQIPYFRAFTMPWTRTRAYPHAFIVPDQKRGGNYNYLTHVL 900
901 FENVFWKGISGQVNKWRVETLGLGKTNLFLLQQNNVPFLYNVSPTIFPPS 950
951 IDFSEWVRVTGYWFLDDKSTFKPPAELQEFISEARSKGKKLVYIGFGSIV 1000
1001 VSNAKEMTEALVEAVMEADVYCILNKGWSERLGDKAAKKTEVDLPRNILN 1050
1051 IGNVPHDWLFPQVDAAVHHGGSGTTGASLRAGLPTVIKPFFGDQFFYAGR 1100
1101 VEDIGVGIALKKLNAQTLADALKVATTNKIMKDRAGLIKKKISKEDGIKT 1150
1151 AISAIYNELEYARSVTLSRVKTPRKKEENVDATKLTPAETTDEGWTMI 1198
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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