 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O89047 from www.uniprot.org...
The NucPred score for your sequence is 0.46 (see score help below)
1 MPAMRGLLAPQNTFLDTIATRFDGTHSNFVLGNAQVAGLFPVVYCSDGFC 50
51 DLTGFSRAEVMQRGCACSFLYGPDTSELVRQQIRKALDEHKEFKAELILY 100
101 RKSGLPFWCLLDVIPIKNEKGEVALFLVSHKDISETKNRGGPDNWKERGG 150
151 GRRRYGRAGSKGFNANRRRSRAVLYHLSGHLQKQPKGKHKLNKGVFGEKP 200
201 NLPEYKVAAIRKSPFILLHCGALRATWDGFILLATLYVAVTVPYSVCVST 250
251 AREPSAARGPPSVCDLAVEVLFILDIVLNFRTTFVSKSGQVVFAPKSICL 300
301 HYVTTWFLLDVIAALPFDLLHAFKVNVYVGAHLLKTVRLLRLLRLLPRLD 350
351 RYSQYSAVVLTLLMAVFALLAHWVACVWFYIGQQEIENSESELPEIGWLQ 400
401 ELARRLETPYYLVSRSPDGGNSSGQSENCSSSGGGSEANGTGLELLGGPS 450
451 LRSAYITSLYFALSSLTSVGFGNVSANTDTEKIFSICTMLIGALMHAVVF 500
501 GNVTAIIQRMYARRFLYHSRTRDLRDYIRIHRIPKPLKQRMLEYFQATWA 550
551 VNNGIDTTELLQSLPDELRADIAMHLHKEVLQLPLFEAASRGCLRALSLA 600
601 LRPAFCTPGEYLIHQGDALQALYFVCSGSMEVLKGGTVLAILGKGDLIGC 650
651 ELPQREQVVKANADVKGLTYCVLQCLQLAGLHESLALYPEFAPRFSRGLR 700
701 GELSYNLGAGGVSAEVDTSSLSGDNTLMSTLEEKETDGEQGHTISPAPAD 750
751 EPSSPLLSPGCTSSSSAAKLLSPRRTAPRPRLGGRGRPSRAGVLKPEAGP 800
801 SAHPRTLDGLQLPPMPWNVPPDLSPRVVDGIEDGCGSDQHKFSFRVGQSG 850
851 PECSSSPSPGTESGLLTVPLVPSEARNTDTLDKLRQAVTELSEQVLQMRE 900
901 GLQSLRQAVQLILVPQGEGQCPRVSGEGPCPATASGLLQPLRVDTGASSY 950
951 CLQPPAGSVLSGTWPHPRPGHPPPLMAPWPWGPPASQSSPWPRATALWTS 1000
1001 TSDSEPPGSGDLCSEPSTPASPPPPEEGARTGTPAPVSQAEATSTGEPPP 1050
1051 GSGGRALPWDPHSLEMVLIGCHGPGSVQWTQEEGTGV 1087
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.) |
Go back to the NucPred Home Page.