 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8WY21 from www.uniprot.org...
The NucPred score for your sequence is 0.79 (see score help below)
1 MGKVGAGGGSQARLSALLAGAGLLILCAPGVCGGGSCCPSPHPSSAPRSA 50
51 STPRGFSHQGRPGRAPATPLPLVVRPLFSVAPGDRALSLERARGTGASMA 100
101 VAARSGRRRRSGADQEKAERGEGASRSPRGVLRDGGQQEPGTRERDPDKA 150
151 TRFRMEELRLTSTTFALTGDSAHNQAMVHWSGHNSSVILILTKLYDYNLG 200
201 SITESSLWRSTDYGTTYEKLNDKVGLKTILSYLYVCPTNKRKIMLLTDPE 250
251 IESSLLISSDEGATYQKYRLNFYIQSLLFHPKQEDWILAYSQDQKLYSSA 300
301 EFGRRWQLIQEGVVPNRFYWSVMGSNKEPDLVHLEARTVDGHSHYLTCRM 350
351 QNCTEANRNQPFPGYIDPDSLIVQDHYVFVQLTSGGRPHYYVSYRRNAFA 400
401 QMKLPKYALPKDMHVISTDENQVFAAVQEWNQNDTYNLYISDTRGVYFTL 450
451 ALENVQSSRGPEGNIMIDLYEVAGIKGMFLANKKIDNQVKTFITYNKGRD 500
501 WRLLQAPDTDLRGDPVHCLLPYCSLHLHLKVSENPYTSGIIASKDTAPSI 550
551 IVASGNIGSELSDTDISMFVSSDAGNTWRQIFEEEHSVLYLDQGGVLVAM 600
601 KHTSLPIRHLWLSFDEGRSWSKYSFTSIPLFVDGVLGEPGEETLIMTVFG 650
651 HFSHRSEWQLVKVDYKSIFDRRCAEEDYRPWQLHSQGEACIMGAKRIYKK 700
701 RKSERKCMQGKYAGAMESEPCVCTEADFDCDYGYERHSNGQCLPAFWFNP 750
751 SSLSKDCSLGQSYLNSTGYRKVVSNNCTDGVREQYTAKPQKCPGKAPRGL 800
801 RIVTADGKLTAEQGHNVTLMVQLEEGDVQRTLIQVDFGDGIAVSYVNLSS 850
851 MEDGIKHVYQNVGIFRVTVQVDNSLGSDSAVLYLHVTCPLEHVHLSLPFV 900
901 TTKNKEVNATAVLWPSQVGTLTYVWWYGNNTEPLITLEGSISFRFTSEGM 950
951 NTITVQVSAGNAILQDTKTIAVYEEFRSLRLSFSPNLDDYNPDIPEWRRD 1000
1001 IGRVIKKSLVEATGVPGQHILVAVLPGLPTTAELFVLPYQDPAGENKRST 1050
1051 DDLEQISELLIHTLNQNSVHFELKPGVRVLVHAAHLTAAPLVDLTPTHSG 1100
1101 SAMLMLLSVVFVGLAVFVIYKFKRRVALPSPPSPSTQPGDSSLRLQRARH 1150
1151 ATPPSTPKRGSAGAQYAI 1168
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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