 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q6PCJ1 from www.uniprot.org...
The NucPred score for your sequence is 0.79 (see score help below)
1 MSVEATGKPLKVGSRVEVIGKGYRGTVAYVGATLFATGKWVGVILDDSKG 50
51 KNDGTVQGRRYFTCEENHGIFVRQSQIQVIEDGADTTSPETPEPTASKGL 100
101 KKDVMETPKSSKLPTRPSSSAASSGTASASCGEISSSEPSTPAQTPLAAP 150
151 IIPSPSSAITSPVAPLPGPGPSKEEENLRAQVKDLEEKLETLKMKRAEDK 200
201 AKLKEMEKSKLQLEQVQEWKSKMQEQQADIQRQLKEAKKEAKEALEAKER 250
251 YMEEMADTADAIEMATLDKEMAEERAESLQQEVDTLKDKVEEHKIDLEIL 300
301 KHEIEEKGSDGAASSYQVKQLEEQNARLKEALVRMRDLSASEKQEHIKVQ 350
351 KQMEKKNTELDTLRQQKEKLQEEASHMEKTIDELKEQVDAALGAEEMVET 400
401 LAERNLDLEEKVRELRETVSDLEAINEMNDELQENARETELELREQLDMA 450
451 GARVREAEKRVEAAQETVADYQQTIKKYRDLTAHLQEVNSELRNQQEASV 500
501 EKEQQPSPEMFDFKIKFAETKAHAKAIEMELRKMEVTQANRHVSLLTSFM 550
551 PDSFLRHGGDHDCILVLLLIPRLICKAELISKQAQEKFELSEVGEQKSGM 600
601 RGAVGEQMSFAAGLVYSLTLLQATLHKYEQALDKCSVEVYKKVGMLYPEM 650
651 SVHERSLDFLIELLHKDQLDETVNVEPLTKAIKYYQHLYSIHLADQAEEC 700
701 TMQLSDHIKFTQSALDCMGVEVSRLRAFLHAGQESSDFAILLKDLETSCS 750
751 DIRQFCKKIRRRMPGTEAAGIPAALGFGQQVCETLLDCRKYLKCVVAVFQ 800
801 EVAAAGAQMIAPMGENEGLQALKLEDVAFKATEQIYGTKGSNPYECLRQS 850
851 CSVVIATMNKMATAMQEGEYDAEKPQSKSPPPVEQRAAALRAEITDAEGL 900
901 GLKLEDRETVIKELKKSLKIKGEELSEANVRLSLLEKKLDSASKEADDRV 950
951 EKIQTKLEETQTVLKKKEKEFEETMDALQADIDQLESEKAELRQRLNNQS 1000
1001 KRTIEGLRGVPASGVASIVSGLAGGVSSGQSLINGSGPVQVKDSPLLLQQ 1050
1051 IDALRLSMKHLKHENNKLKAHQIKTDLSSLPALHVPKLTLPKDRQKEEAM 1100
1101 SGTLYRKTSQLLDALQQMSANAKVVDITHKKAGNPAAQLLEQTARLKSLS 1150
1151 DTIDKLKNEVMKETVSQCPGANVPTDFATFPSTDFIKAKEEKKEDTVYIG 1200
1201 KVTLSCQPGQGQIHKLVLTPEQLHELHERLIC 1232
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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