 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q91012 from www.uniprot.org...
The NucPred score for your sequence is 0.57 (see score help below)
1 MFPRRGSSSSSGSSCVTAPTAPGTGVGSAALSAEDYQPPLLVQPPPPSPA 50
51 ASSSAGPQPTPPPPQSLNLLSQSQLQPQPLAQTGAQMKKKSGFQITSVTP 100
101 AQISASMSSNNSIAEDTESYDDLDESHTEDLSSSEILDVSLSRATDLGEP 150
151 ERSSSEETLNNFQEAETPGAVSPNQPHLPQQHPSLPHHPQQSVVINGSVH 200
201 PHHVHHHHHLHHHHHGHHHPSHPGVGSAPVSAGPPPSPSFRKLSTTGSSD 250
251 NVISAAPGSAASSTGSPASVVSNIRTTSTPGNLGVSSATGTSTLNNMGAG 300
301 SSSVASSMLGAMNLSNITSTGNVNALSGTSGNVNVNILSGVGNGTSASSS 350
351 VVNNVTNPSAGVAAGSSQQQPASGTSRFRVVKLDSSSDPFKKGRWTCTEF 400
401 YDKENTVAASEGVAVNKAVETIKQNPLEVTSERESTSGSSVSSNVSTLSH 450
451 YTESVGSGEMGAPTVVQQQASQGVGPQQMDFSSTAPPAIPASSIPQSVSQ 500
501 SQLAQVQLHSQEINYPQEKPGVQPPAQASLTTVTGVQPAPVNLLGVSPAL 550
551 GHQQPAIQSMAQQELPYSQPAQPVQTLPVVQQQQLQYGQQQQQQQAVPTQ 600
601 MATGHVKSVNQNSVTGAVSEYIQHQQILQPPAPAMQPSPAGVGGGPPVPV 650
651 AQAPSMQSAVPVHPAAAPAQPVAHAPAAIPGVGTSGQMLSVGQQANVAAV 700
701 VYPPPAANQIPPPVMPSTAAPPSSQVVQPVQTGIMQQGLQASASGLPQQM 750
751 VIAQQNTLLPVQPQAQAVESVVQGMTGQQLPAVSPIPSASTVPAPSQAGS 800
801 AVPPGIPSASIGLGQPQNIAQASAVQNGNLAQSVSQPPLVSTSIGMPVAP 850
851 SVPQQIPLSSTQFPAQSLAQPVVSQMEDGRRPTEPSLVGLPQAASGESSV 900
901 GASDIADGGSSNVPASVSLFPLKVLPLATPLVDGEDESSSGASVVAIDNK 950
951 IEQAMDLVKSHLMYAVREEVEVLKEQIKELIEKNSQLEQENTLLKTLASP 1000
1001 EQLAQFQAQLQTGSPPSSGQAQGTAQQPAQPASQGSGPSA 1040
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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