 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9JKA7 from www.uniprot.org...
The NucPred score for your sequence is 0.71 (see score help below)
1 MDKLPPSMRKRLYSLPQQVGAKAWIMDEEEDGEEEGAGGLQDPSRRSIRL 50
51 RPLPSPSPSVAAGCSESRGAALGAADSEGPGRSAGKSSTNGDCRRFRGSL 100
101 ASLGSRGGGSGGAGGGSSLGHLHDSAEERRLIAAEGDASPGEDRTPPGLA 150
151 TEPERPGAAAQPAASPPPQQPPQPASASCEQPSADTAIKVEGGAAASDQI 200
201 LPEAEVRLGQSGFMQRQFGAMLQPGVNKFSLRMFGSQKAVEREQERVKSA 250
251 GFWIIHPYSDFRFYWDLTMLLLMVGNLIIIPVGITFFKDENTTPWIVFNV 300
301 VSDTFFLIDLVLNFRTGIVVEDNTEIILDPQRIKMKYLKSWFVVDFISSI 350
351 PVDYIFLIVETRIDSEVYKTARALRIVRFTKILSLLRLLRLSRLIRYIHQ 400
401 WEEIFHMTYDLASAVVRIVNLIGMMLLLCHWDGCLQFLVPMLQDFPHDCW 450
451 VSINGMVNNSWGKQYSYALFKAMSHMLCIGYGRQAPVGMSDVWLTMLSMI 500
501 VGATCYAMFIGHATALIQSLDSSRRQYQEKYKQVEQYMSFHKLPPDTRQR 550
551 IHDYYEHRYQGKMFDEESILGELSEPLREEIINFNCRKLVASMPLFANAD 600
601 PNFVTSMLTKLRFEVFQPGDYIIREGTIGKKMYFIQHGVVSVLTKGNKET 650
651 KLADGSYFGEICLLTRGRRTASVRADTYCRLYSLSVDNFNEVLEEYPMMR 700
701 RAFETVALDRLDRIGKKNSILLHKVQHDLNSGVFNYQENEIIQQIVRHDR 750
751 EMAHCAHRVQAAASATPTPTPVIWTPLIQAPLQAAAATTSVAIALTHHPR 800
801 LPAAIFRPPPGPGLGNLGAGQTPRHPRRLQSLIPSALGSASPASSPSQVD 850
851 TPSSSSFHIQQLAGFSAPPGLSPLLPSSSSSPPPGACSSPPAPTPSTSTA 900
901 ATTTGFGHFHKALGGSLSSSDSPLLTPLQPGARSPQAAQPPPPLPGARGG 950
951 LGLLEHFLPPPPSSRSPSSSPGQLGQPPGELSPGLAAGPPSTPETPPRPE 1000
1001 RPSFMAGASGGASPVAFTPRGGLSPPGHSPGPPRTFPSAPPRASGSHGSL 1050
1051 LLPPASSPPPPQVPQRRGTPPLTPGRLTQDLKLISASQPALPQDGAQTLR 1100
1101 RASPHSSGESMAAFSLYPRAGGGSGSSGGLGPPGRPYGAIPGQHVTLPRK 1150
1151 TSSGSLPPPLSLFGARAASSGGPPLTAAPQREPGARSEPVRSKLPSNL 1198
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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