 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9ER47 from www.uniprot.org...
The NucPred score for your sequence is 0.92 (see score help below)
1 MPVRRGHVAPQNTFLGTIIRKFEGQNKKFIIANARVQNCAIIYCNDGFCE 50
51 MTGFSRPDVMQKPCTCDFLHGPETKRHDIAQIAQALLGSEERKVEVTYYH 100
101 KNGSTFICNTHIIPVKNQEGVAMMFIINFEYVTDEENAATPERVNPILPV 150
151 KTVNRKLFGFKFPGLRVLTYRKQSLPQEDPDVVVIDSSKHSDDSVAMKHF 200
201 KSPTKESCSPSEADDTKALIQPSQCSPLVNISGPLDHSSPKRQWDRLYPD 250
251 MLQSSSQLTHSRSRESLCSIRRASSVHDIEGFSVHPKNIFRDRHASEDNG 300
301 RNVKGPFNHIKSSLLGSTSDSNLNKYSTINKIPQLTLNFSDVKTEKKNTS 350
351 PPSSDKTIIAPKVKERTHNVTEKVTQVLSLGADVLPEYKLQTPRINKFTI 400
401 LHYSPFKAVWDWLILLLVIYTAIFTPYSAAFLLNDREEQKRRECGYSCSP 450
451 LNVVDLIVDIMFIIDILINFRTTYVNQNEEVVSDPAKIAIHYFKGWFLID 500
501 MVAAIPFDLLIFGSGSDETTTLIGLLKTARLLRLVRVARKLDRYSEYGAA 550
551 VLMLLMCIFALIAHWLACIWYAIGNVERPYLTDKIGWLDSLGTQIGKRYN 600
601 DSDSSSGPSIKDKYVTALYFTFSSLTSVGFGNVSPNTNSEKIFSICVMLI 650
651 GSLMYASIFGNVSAIIQRLYSGTARYHMQMLRVKEFIRFHQIPNPLRQRL 700
701 EEYFQHAWTYTNGIDMNMVLKGFPECLQADICLHLNQTLLQNCKAFRGAS 750
751 KGCLRALAMKFKTTHAPPGDTLVHCGDVLTALYFLSRGSIEILKDDIVVA 800
801 ILGKNDIFGEMVHLYAKPGKSNADVRALTYCDLHKIQREDLLEVLDMYPE 850
851 FSDHFLTNLELTFNLRHESAKSQSVNDSEGDTGKLRRRRLSFESEGEKDF 900
901 SKENSANDADDSTDTIRRYQSSKKHFEERKSRSSSFISSIDDEQKPLFLG 950
951 TVDSTPRMVKATRLHGEETMPHSGRIHTEKRSHSCRDITDTHSWEREPAR 1000
1001 AQPEECSPSGLQRAAWGVSETESDLTYGEVEQRLDLLQEQLNRLESQMTT 1050
1051 DIQAILQLLQKQTTVVPPAYSMVTAGAEYQRPILRLLRTSHPRASIKTDR 1100
1101 SFSPSSQCPEFLDLEKSKLQSKESLSSGRRLNTASEDNLTSLLKQDSDAS 1150
1151 SELDPRQRKTYLHPIRHPSLPDSSLSTVGILGLHRHVSDPGLPGK 1195
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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