| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9ESC8 from www.uniprot.org...
The NucPred score for your sequence is 0.95 (see score help below)
1 MNREDRNVLRMKERERRNQEIQQGEDAFPPSSPLFAEPYKVTSKEDKLSS 50
51 RIQSMLGNYDEMKDYIGDRSIPKLVAIPKPAVPTTTDEKANPNFFEQRHG 100
101 GSHQSSKWTPVGPAPSTSQSQKRSSALQSGHSSQRSGAGGSGASSSGQRH 150
151 DRDSYSSSRKKGQHGSEHSKSRSSSPGKPQAVSSLSSSHSRSHGNDHHSK 200
201 EHQRSKSPRDPDANWDSPSRGPFSSGQHSSQSFPPSLMSKSSSMLQKPTA 250
251 YVRPMDGQESVEPKLSSEHYSSQSHGNSMTELKPSSKAHLTKLKIPSRPL 300
301 DASVSGDVSCVDEILKEMTHSWPPPLTAIHTPCKTEPSKFPFPTKESQQS 350
351 NFGPGEQKRYSTAKTSNGHQSKSMLKDDLKLSSSEDSDGEQDCDKTMPRS 400
401 TPGSNSEPSHHNSEGADNSRDDSSSHSGSESSSGSDSESESSSSDSEANE 450
451 PSQSASPEPEPPPTNKWQLDNWLNKVNPHKVSPASSVDSNIPSSQAYKKE 500
501 GREQGTASNYTDPGGTKETSSATPGRDSKTIQKGSESGRGRQKSPAQSDS 550
551 TTQRRTVGKKQPKKPEKSAAEEPRGGLKIESETPVDMAASMPSSRHKAAT 600
601 KGSRKPNIKKESKSSPRPTAEKKKYKSASKPSQKSREIIETDTSSSDSDG 650
651 SESLPPSSQTPKYPESNRTPVKPSSVEEEDSFFRQRMFSPMEEKELLSPL 700
701 SEPDDRYPLIVKIDLNLLTRIPGKPYKETEPPKGEKKNVPEKHSREVQKQ 750
751 ASEKASNKGKRKHKNDDDTRASESKKPKTEDKNSSGHKPSSSRESSKQSS 800
801 TKEKDLLPSPAGPILSKDSKTEHGSRKRTVSQSSSLKSSGTSSKENSGSS 850
851 SKSSSSSTAKQKKTEGKGPSSSKEAKEKAPNSSSNCPPSTPTSESSKPRR 900
901 TKLAFDDRNYSADHYLQEAKKLKHNADALSDRFEKAVYYLDAVVSFIECG 950
951 NALEKNAQESKSPFPMYSDTVELIKYTMKLKNYLAPDATAADKRLTVLCL 1000
1001 RCQSLLYLRLFKLKKENALKYSKTLTEHLKNSYSNSQAPSPGLGSKAVGM 1050
1051 PSPVSPKLSPGNSGSYSSGGSSASASGSSVTIPQKIHQMAASYVQVTSNF 1100
1101 LYATEIWDQAEQLSKEQKEFFAELDKVMGPLIFNASIMTDLARYTRQGLH 1150
1151 WLRQDAKLIS 1160
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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