 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q61543 from www.uniprot.org...
The NucPred score for your sequence is 0.85 (see score help below)
1 MAVCGRVRGMFRLSAALPLLLLAAAGAQNGHGQGQGPGTNFGPFPGQGGG 50
51 GSPAGQQPPQQPQLSQQQQQPPPQQQQQQQQQSLFAAGGLPARRGGAGPG 100
101 GTGGGWKLAEEESCREDVTRVCPKHTWSNNLAVLECLQDVREPENEISSD 150
151 CNHLLWNYKLNLTTDPKFESVAREVCKSTISEIKECAEEPVGKGYMVSCL 200
201 VDHRGNITEYQCHQYITKMTAIIFSDYRLICGFMDDCKNDINLLKCGSIR 250
251 LGEKDAHSQGEVVSCLEKGLVKEAEEKEPKIQVSELCKKAILRVAELSSD 300
301 DFHLDRHLYFACRDDRERFCENTQAGEGRVYKCLFNHKFEESMSEKCREA 350
351 LTTRQKLIAQDYKVSYSLAKSCKSDLKKYRCNVENLPRSREARLSYLLMC 400
401 LESAVHRGRQVSSECQGEMLDYRRMLMEDFSLSPEIILSCRGEIEHHCSG 450
451 LHRKGRTLHCLMKVVRGEKGNLGMNCQQALQTLIQETDPGADYRIDRALN 500
501 EACESVIQTACKHIRSGDPMILSCLMEHLYTEKMVEDCEHRLLELQYFIS 550
551 RDWKLDPVLYRKCQGDASRLCHTHGWNETSELMPPGAVFSCLYRHAYRTE 600
601 EQGRRLSRECRAEVQRILHQRAMDVKLDPALQDKCLIDLGKWCSEKTETG 650
651 QELECLQDHLDDLAVECRDIVGNLTELESEDIQIEALLMRACEPIIQNFC 700
701 HDVADNQIDSGDLMECLIQNKHQKDMNEKCAIGVTHFQLVQMKDFRFSYK 750
751 FKMACKEDVLKLCPNIKKKVDVVICLSTTVRNDTLQEAKEHRVSLKCRKQ 800
801 LRVEELEMTEDIRLEPDLYEACKSDIKNYCSTVQYGNAQIIECLKENKKQ 850
851 LSTRCHQKVFKLQETEMMDPELDYTLMRVCKQMIKRFCPEADSKTMLQCL 900
901 KQNKNSELMDPKCKQMITKRQITQNTDYRLNPVLRKACKADIPKFCHGIL 950
951 TKAKDDSELEGQVISCLKLRYADQRLSSDCEDQIRIIIQESALDYRLDPQ 1000
1001 LQLHCSDEIANLCAEEAAAQEQTGQVEECLKVNLLKIKTELCKKEVLNML 1050
1051 KESKADIFVDPVLHTACALDIKHHCAAITPGRGRQMSCLMEALEDKRVRL 1100
1101 QPECKKRLNDRIEMWSYAAKVAPADGFSDLAMQVMTSPSKNYILSVISGS 1150
1151 ICILFLIGLMCGRITKRVTRELKDR 1175
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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