 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q5M9F1 from www.uniprot.org...
The NucPred score for your sequence is 0.80 (see score help below)
1 MALRGEGRKRKKGQERRQSSEDDVGNAATDYLVGQVADSLRGGARPPGGG 50
51 TGRLAALFSTPETLAPPVFVPVPQETSKKRKPDDEEETVAHIKKPALQEP 100
101 ARKVKVKKLSDADKRLANRESALANADLEEIRQDQGQGRRRSQSRGKVTD 150
151 GEALDVALSLNEDGRQRTKVPLNPEEERLKNERTVFVGNLPVTCNKKKLK 200
201 SFFKEYGQVESVRFRSVMPAEGTLSKKLAAIKRKFHPDQKSINAYVVFKE 250
251 ERAAAKALQRNGAQIAEGFRIRVDLASETASRDKRSVFVGNLPYRVDESA 300
301 LEEHFLDCGSIVAVRIVRNPLTGVGRGFGYVLFENTDAVHLALKLNNSEL 350
351 MGRKLRVMRSVNKEKLKQQNSNPSVKKDGSKSKQRLNFTSKEGKSHSKNA 400
401 FIGEKAVLMKKKKGQKKKGQTKKPRKQK 428
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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