 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P30315 from www.uniprot.org...
The NucPred score for your sequence is 0.63 (see score help below)
1 MEELKTCPFTNVIPYGLLYDKLKKEKNNDVPENYVIEEFDKLLKNYERPN 50
51 VYDEIGNATFKNDEDLITFQIDLDYTVENIFKNMIYNESGSNNSILNDIY 100
101 MPYRILLSKDKNYVSVPIIRIYSLRKDGCSVLINVHNFFPYFYVEKPDDF 150
151 DNEDLIKLEMLMNENLNLNSQYKIYEKKILKIEIVKTESLMYFKKNGKKD 200
201 FLKITVLLPKMVPSLKKYFEGIVHVNNKSIGGIVYEANLPFILRYIIDHK 250
251 ITGSSWINCKKGHYYIRNKNKKISNCTFEIDISYEHVEPITLENEYQQIP 300
301 KLRILSFDIECIKLDGKGFPEAKNDPIIQISSILYFQGEPIDNCTKFIFT 350
351 LLECASIPGSNVIWFNDEKTLLEAWNEFIIRIDPDFLTGYNIINFDLPYI 400
401 LNRGTALNLKKLKFLGRIKNVASTVKDSSFSSKQFGTHETKEINIFGRIQ 450
451 FDVYDLIKRDYKLKSYTLNYVSFEFLKEQKEDVHYSIMNDLQNESPESRK 500
501 RIATYCIKDGVLPLRLIDKLLFIYNYVEMARVTGTPFVYLLTRGQQIKVT 550
551 SQLYRKCKELNYVIPSTYMKVNTNEKYEGATVLEPIKGYYIEPISTLDFA 600
601 SLYPSIMIAHNLCYSTLIKSNHEVSDLQNDDITTIQGKNNLKFVKKNVKK 650
651 GILPLIVEELIEARKKVKLLIKNEKNNITKMVLNGRQLALKISANSVYGY 700
701 TGASSGGQLPCLEVAVSITTLGRSMIEKTKERVESFYCKSNGYEHNSTVI 750
751 YGDTDSVMVKFGTNNIEEAMTLGKDAAERISKEFLSPIKLEFEKVYCPYL 800
801 LLNKKRYAGLLYTNPNKHDKMDCKGIETVRRDFCILIQQMMETVLNKLLI 850
851 EKNLNSAIEYTKSKIKELLTNNIDMSLLVVTKSLGKTDYETRLPHVELAK 900
901 KLKQRDSATAPNVGDRVSYIIVKGVKGQAQYERAEDPLYVLDNNLAIDYN 950
951 HYLDAIKSPLSRIFEVIMQNSDSLFSGDHTRHKTILTSSQTALSKFLKKS 1000
1001 VRCIGCNSSIKKPPLCNHCKENKEFSIYMQKIKDFKNKQNEFFQLWTECQ 1050
1051 RCQGNLHVDVICMNRDCPIFYRRAKIKKDIANLQEQVTSLRMDW 1094
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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