| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q6DEU9 from www.uniprot.org...
The NucPred score for your sequence is 0.96 (see score help below)
1 MSRGSIEIPLRDTDEVIELDFDQLPEGDEVISILKQEHTQLHIWIALGLE 50
51 YYKQVKTEDFVKLLEAARIDGNLDYRDHEKDQMTCLDTLAAYYVQQARKE 100
101 KNKDNKKELITQATLLYTMADKIIMYDQNHLLGRACFCLLEGDKMDQADA 150
151 QFHFVLNQSPNNIPALLGKACISFNKKDYRGALAYYKKALRTNPGCPAGV 200
201 RLGMGHCFVKLNKLDKARLAFGRALDLNPTCVGALVGLAVLELNNKEADS 250
251 IKNGVQLLSKAYTIDPSNPMVLNHLANHFFFKKDYSKVQHLALHAFHNTE 300
301 VEAMQAESCYQLARSFHVQEDYDQAFQYYYQATQFAAASFVLPFFGLGQM 350
351 YIYRGDKENASQCFEKVLKAYPNNYETMKILGSLYAASDDQEKRDIAKSH 400
401 LKKVTEQYPDDVEAWIELAQILEQTDIQNALSAYGTATRILQEKVQADVP 450
451 PEILNNVGALHFRLGNLGEAKKYFLASLDRAKAEAEHDEHYYNAISVTTT 500
501 YNLARLYEGLCEFHESEKLYKNILREHPNYVDCYLRLGAMARDKGNFYEA 550
551 SDWFKEALQINQDHPDAWSLIGNLHLAKQEWGPGQKKFERILKQPSTQND 600
601 TYSMLALGNVWLQTLHQPTRDREKEKRHQDRALAIYKQVLRNDSKNLYAA 650
651 NGIGAVLAHKGYVREARDVFAQVREATADISDVWLNLAHIYVEQKQYISA 700
701 VQMYENCLRKFYKHQNTEVLLYLARALFKCGKLQECKQILLKARHVAPND 750
751 TVLMFNVALVLQRLATLVLKDEKSNLKAVLNAVKELELAHRYFNYLSKVG 800
801 DKMRFDLALAASEARQCSDLLSQAQYHVARARKQDEEEKELRAKQEQEKE 850
851 ILRQKLIKEQEEKRLKEIEEQKKLLEQRAQYVEKTRNLLNFTGEMETPKE 900
901 KKQRGGGGGGGGRRSKKNGEFDEFVNDDSDEDLAPRKKKRKKGGGSSGSG 950
951 GEQGEGGEEGEGGEKKKKKRRKRPQKGGDGSDDDEDQAPQPKKRQPKKRE 1000
1001 KPAKFERTPPSMKGKIKSKAIISSSEDDSDEDKLKIADEGHGRGSNSDSD 1050
1051 EGPRTQAKKRIMSDSDSDNANKSGSGAGSPQKSPQSDGDSDNNAWARKRR 1100
1101 RQDSGSDNDSAQSRRSSGGSDNESRAASRSPESQRGSDRGSDNEGSARAS 1150
1151 PNESEQEASNNEKSDRGSDDSD 1172
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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