| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P60469 from www.uniprot.org...
The NucPred score for your sequence is 0.93 (see score help below)
1 MMCEVMPTISEDGRRGSALGPDEAGGELERLMVTMLTERERLLETLREAQ 50
51 DGLATAQLRLRELGHEKDSLQRQLSIALPQEFAALTKELNLCREQLLERE 100
101 EEIAELKAERNNTRLLLEHLECLVSRHERSLRMTVVKRQAQSPGGVSSEV 150
151 EVLKALKSLFEHHKALDEKVRERLRMALERVAVLEEELELSNQEALNLRD 200
201 QLSRRRSGLEEPGKDGDGQTLANGLGPVGESNRRTAELEEALERQRAEVC 250
251 QLRERLAVLCRQMSQLEEELGTAHRELGKAEEANSKLQRDLKEALAQRED 300
301 MEERITTLEKRYLSAQREATSLHDANDKLENELASKESLYRQSEEKSRQL 350
351 AEWLDDAKQKLQQTLQKAETLPEIEAQLAQRVAALNKAEERHGNFEERLR 400
401 QLEAQLEEKNQELQRARQREKMNDDHNKRLSETVDKLLSESNERLQLHLK 450
451 ERMGALEEKNSLSEEIANMKKLQDELLLNKEQLLAEMERMQMEIDQLRGR 500
501 PPSSYSRSLPGSALELRYSQAPTLPSGAPLDPYGAGSGRAGKRGRWSGAK 550
551 DESSKDWDRSAPAGSIPPPFPGELDGSDEEEAEGMFGAELLSPSGQADVQ 600
601 TLAIMLQEQLEAINKEIKLIQEEKETTEQRAEELESRVSSSGLDSLGRYR 650
651 SSCSLPPSLTTSTLASPSPPSSGHSTPRLAPPSPAREGTDKTNHVSKEEA 700
701 GVPRGEGPAVPGDTPPPTPRSARLERMAQALALQAGSPEDGAPPRGSEST 750
751 PDSLHKAPKRKSIKSSIGRLFGKKEKGRMGPPGRESVSLAGTPSDETLAT 800
801 DPLGLAKLTGPGDKDRRNKRKHELLEEACRQGLPFAAWDGPTVVSWLELW 850
851 VGMPAWYVAACRANVKSGAIMANLSDTEIQREIGISNPLHRLKLRLAIQE 900
901 MVSLTSPSAPASSRTPTGNVWMTHEEMESLTAATKPETKEISWEQILAYG 950
951 DMNHEWVGNDWLPSLGLPQYRSYFMESLVDARMLDHLNKKELRGQLKMVD 1000
1001 SFHRVSLHYGIMCLKRLNYDRKDLERRREESQTQIRDVMVWSNERVMGWV 1050
1051 SGLGLKEFATNLTESGVHGALLALDETFDYSDLALLLQIPTQNAQARQLL 1100
1101 EKEFSNLISLGTDRRLDEDSAKSFSRSPSWRKMFREKDLRGVTPDSAEML 1150
1151 PPNFRSAAAGALGSPGLPLRKLQPEGQTSGSSRADGVSVRTYSC 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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