 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q2KNA0 from www.uniprot.org...
The NucPred score for your sequence is 0.91 (see score help below)
1 MKKASRSVGSVPKVSGISKTQTVEKTKPENSSSASTGGKVIKTGTTASLS 50
51 KTKSSDDLLAGMAGGVTVTNGVKGKKSTCPSTGSSASAPAMTTVENKSKI 100
101 STGTSSSTKRSTSIGNKESSSTRERLRERTRLNQSKKLPSAGQGANDVAL 150
151 AKRSRSRTTTECDVRMSKSKSDNQISDKAALEAKVKDLLTLAKTKDVEIL 200
201 HLRNELRDMRAQLGINEDHSEGDEKSEKEAIIAHQPTDVESTLLQLQEQN 250
251 TAIREELNQLKNENRMLKDRLNALGFSLEQRLDNSEKLFGYQSLSPEITP 300
301 GNQSDGGGTLTSSVEGSAPGSVEDLLSQDENTLMDHQHSNSMDNLDSECS 350
351 EVYQPLTSSDDALDAPSSSESEGIPSIERSRKGSSGNASEVSVACLTERI 400
401 HQMEENQHSTSEELQATLQELADLQQITQELNSENERLGEEKVILMESLC 450
451 QQSDKLEHFSRQIEYFRSLLDEHHISYVIDEDVKSGRYMELEQRYMDLAE 500
501 NARFEREQLLGVQQHLSNTLKMAEQDNKEAQEMIGALKERNHHMERIIES 550
551 EQKGKAALAATLEEYKATVASDQIEMNRLKAQLENEKQKVAELYSIHNSG 600
601 DKSDIQDLLESVRLDKEKAETLASSLQEDLAHTRNDANRLQDTIAKVEDE 650
651 YRAFQEEAKKQIEELNMTLEKLRSELEEKETERSDMKETIFELEDEVEQH 700
701 RAVKLHDNLIISDLENTVKKLQDQKHDMEREIKTLHRRLREESAEWRQFQ 750
751 ADLQTAVVIANDIKSEAQEEIGDLKRRLHEAQEKNEKLTKELEEIKSRKQ 800
801 EEERGRVYNYMNAVERDLAALRQGMGLSRRSSTSSEPTPTVKTLIKSFDS 850
851 ASQVPNPTAAAIPRTPLSPSPMKTPPAAAVSPMQRHSISGPISTSKPLTA 900
901 LSDKRPNYGEIPVQEHLLRTSSTSRPASLPRVPAMESAKTISVSRRSSEE 950
951 MKRDISAPEGASPASLMAMGTTSPQLSLSSSPTASVTPTTRSRIREERKD 1000
1001 PLSALAREYGGSKRNALLKWCQKKTEGYQNIDITNFSSSWNDGLAFCALL 1050
1051 HTYLPAHIPYQELNSQDKRRNFTLAFQAAESVGIKSTLDINEMVRTERPD 1100
1101 WQSVMLYVTAIYKYFET 1117
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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