 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q2KN98 from www.uniprot.org...
The NucPred score for your sequence is 0.90 (see score help below)
1 MKKANRSAGSVPKVSGISKPQTVEKSKPENSSSAPTGVKPVRPGAAAALS 50
51 KTKSNDDLLAGMAGGVNVTNGIKAKKSTCSSAAPSAPAPAMTISENKSKI 100
101 STGTSSSAKRSTSAGNKESSSTRERLRERTRLNQSKKLPSVSQGANDVAL 150
151 AKRSRSRTAAEGDIRMSKSKSDNQISDKAALEAKVKDLLTLAKTKDVEIL 200
201 HLRNELRDMRAQLGISEDHCEGEDRSEVKETIIAHQPTDVESTLLQLQEQ 250
251 NTAIREELNQLKNENRMLKDRLNALGFSLEQRLDNSEKLFGYQSLSPEIT 300
301 PGNQSDGGGTLTSSVEGSAPGSVEDLLSQDENTLMDHQHSNSMDNLDSEC 350
351 SEVYQPLTSSDDALDAPSSSESEGVPSIERSRKGSSGNASEVSVACLTER 400
401 IHQMEENQHSTSEELQATLQELADLQQITQELNSENERLGEEKVILMESL 450
451 CQQSDKLEHFGRQIEYFRSLLDEHHISYVIDEDVKSGRYMELEQRYMDLA 500
501 ENARFEREQLLGVQQHLSNTLKMAEQDNKEAQEMIGALKERSHHMERIIE 550
551 SEQKGKAALAATLEEYKATVASDQIEMNRLKAQLENEKQKVAELYSIHNS 600
601 GDKSDIQDLLESVRLDKEKAETLASSLQEDLAHTRNDANRLQDTIAKVED 650
651 EYRAFQEEAKKQIEDLNMTLEKLRSELEEKDTERSDMKETIFELEDEVEQ 700
701 HRAVKLHDNLIISDLENTVKKLQDQKHDMEREIKTLHRRLREESAEWRQF 750
751 QADLQTAVVIANDIKSEAQEEIGDLKRRLHEAQEKNEKLTKELEEIKSRK 800
801 QEEERGRVYNYMNAVERDLAALRQGMGLSRRSSTSSEPTPTVKTLIKSFD 850
851 SASQVPNAAAAAIPRTPLSPSPMKTPPAAAVSPMQRHSISGPISTSKPLT 900
901 ALSDKRSNYGELPVQEHLLRTSSTSRPASLPRVPAMESAKTISVSRRSSE 950
951 EMKRDISASEGASPASLMAMGTTSPQLSLSSSPTASVTPSTRSRIREERK 1000
1001 DPLSALAREYGGSKRNALLKWCQKKTEGYQNIDITNFSSSWNDGLAFCAL 1050
1051 LHTYLPAHIPYQELNSQDKKRNFTLAFQAAESVGIKSTLDINEMARTERP 1100
1101 DWQNVMLYVTAIYKYFET 1118
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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