 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9ULD8 from www.uniprot.org...
The NucPred score for your sequence is 0.46 (see score help below)
1 MPAMRGLLAPQNTFLDTIATRFDGTHSNFVLGNAQVAGLFPVVYCSDGFC 50
51 DLTGFSRAEVMQRGCACSFLYGPDTSELVRQQIRKALDEHKEFKAELILY 100
101 RKSGLPFWCLLDVIPIKNEKGEVALFLVSHKDISETKNRGGPDRWKETGG 150
151 GRRRYGRARSKGFNANRRRSRAVLYHLSGHLQKQPKGKHKLNKGVFGEKP 200
201 NLPEYKVAAIRKSPFILLHCGALRATWDGFILLATLYVAVTVPYSVCVST 250
251 AREPSAARGPPSVCDLAVEVLFILDIVLNFRTTFVSKSGQVVFAPKSICL 300
301 HYVTTWFLLDVIAALPFDLLHAFKVNVYFGAHLLKTVRLLRLLRLLPRLD 350
351 RYSQYSAVVLTLLMAVFALLAHWVACVWFYIGQREIESSESELPEIGWLQ 400
401 ELARRLETPYYLVGRRPAGGNSSGQSDNCSSSSEANGTGLELLGGPSLRS 450
451 AYITSLYFALSSLTSVGFGNVSANTDTEKIFSICTMLIGALMHAVVFGNV 500
501 TAIIQRMYARRFLYHSRTRDLRDYIRIHRIPKPLKQRMLEYFQATWAVNN 550
551 GIDTTELLQSLPDELRADIAMHLHKEVLQLPLFEAASRGCLRALSLALRP 600
601 AFCTPGEYLIHQGDALQALYFVCSGSMEVLKGGTVLAILGKGDLIGCELP 650
651 RREQVVKANADVKGLTYCVLQCLQLAGLHDSLALYPEFAPRFSRGLRGEL 700
701 SYNLGAGGGSAEVDTSSLSGDNTLMSTLEEKETDGEQGPTVSPAPADEPS 750
751 SPLLSPGCTSSSSAAKLLSPRRTAPRPRLGGRGRPGRAGALKAEAGPSAP 800
801 PRALEGLRLPPMPWNVPPDLSPRVVDGIEDGCGSDQPKFSFRVGQSGPEC 850
851 SSSPSPGPESGLLTVPHGPSEARNTDTLDKLRQAVTELSEQVLQMREGLQ 900
901 SLRQAVQLVLAPHREGPCPRASGEGPCPASTSGLLQPLCVDTGASSYCLQ 950
951 PPAGSVLSGTWPHPRPGPPPLMAPWPWGPPASQSSPWPRATAFWTSTSDS 1000
1001 EPPASGDLCSEPSTPASPPPSEEGARTGPAEPVSQAEATSTGEPPPGSGG 1050
1051 LALPWDPHSLEMVLIGCHGSGTVQWTQEEGTGV 1083
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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