 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q92351 from www.uniprot.org...
The NucPred score for your sequence is 0.78 (see score help below)
1 MSERDFNTQSPKFKDENANSVISQSDFLGKSLKNNNDDYSDFRGSYLNDK 50
51 SSFQTPLRNGSYQPKGSLEFTPLLQSSNKNSDKYNGSLGDKGSFDPNSYG 100
101 LSAISKQATQEALSISQGNDSYDVSKLTDLSKNSEIDHTDGELPANAALT 150
151 LREQEKVLEKVSRENFGLRIKIVCLEKRLESMAPEQIKEAVKDNVELHAE 200
201 RANLQLQLKRTESLLQKSEDKNFKLEEKVDYLSKVNDVEQSQNVKVFTER 250
251 IRFLENALEKVQREKDSLSTEMEEDKSNKEVDYEYEIRQLQNRLDELSEE 300
301 LDVAQDLLTEKEDEIATLKRQIEEKENSSSAFENEENSSYVHLQEDYAIL 350
351 QAKCDEFADRIQVLTADLEKEKENQIMHESEASIGLTDSMQVHTLQEQLH 400
401 KANEEIEFLHDQISRMNEEGKNFEDIMLQFRSLEEERDVLESKLQTLEDD 450
451 NNSLRLMTSSLGNQIESLRTQNREIDEEKNHLRLLASKNSDKALAETNIR 500
501 LQEVTKELETLRMKNSNDLNEIHDLREENEGLTLKIDSITKEKDRLINEL 550
551 EQRIKSYEVNVSELNGTIDEYRNKLKDKEETYNEVMNAFQYKDNDLRRFH 600
601 ESINKLQDREKELTSNLEKKNLVISSLRETVAMLEKERESIKKYLSGNAK 650
651 DLDNTNLMEILNDKISVLQRQLTDVKDELDVSEEEREEAIVAGQKLSASF 700
701 ELMSNEKQALELKYSSLKNELINAQNLLDRREEELSELSKKLFEERKIRS 750
751 GSNDDIEKNKEINVLNSELADKLAQIRHLESDKMELDKLVHHLNRGIEEA 800
801 NIEENAVKKRLCLLMGCDYSSVSILQIVSQIEHFVNQQIQTIRSLKQELR 850
851 HDFVQFSGKKEQELSRSFEKFGLGTETKHDILAQRNRNVSEKMNDLENAA 900
901 QKFFSSPDRKNGYLYPSEHTSKIEYLEKTIEDLKLALQDELKNRNLLMDD 950
951 ISSYNKQTTKLQEKIKWLERERSILIDELESYRSNQFNYQNNLVQDKNEL 1000
1001 EERLKEIQKELEVYNNHFMKQAELMTSNVTDESQLMLKTLREALQSKTNN 1050
1051 IDHLSTILERNRKEYKSLLDDYNQLRARYKNLQSNTPQSTQSGQYESEIK 1100
1101 GLSKLTKYLQSKCRREHSLRLDLAFSKKFILMQLTGYETCNKINLRMLQK 1150
1151 IGISPDPDLSKKHIKLKSLIIVVCSIERMKRMKNEWLKQAQLKQSLQRAA 1200
1201 AKAKTANY 1208
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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