 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P08518 from www.uniprot.org...
The NucPred score for your sequence is 0.59 (see score help below)
1 MSDLANSEKYYDEDPYGFEDESAPITAEDSWAVISAFFREKGLVSQQLDS 50
51 FNQFVDYTLQDIICEDSTLILEQLAQHTTESDNISRKYEISFGKIYVTKP 100
101 MVNESDGVTHALYPQEARLRNLTYSSGLFVDVKKRTYEAIDVPGRELKYE 150
151 LIAEESEDDSESGKVFIGRLPIMLRSKNCYLSEATESDLYKLKECPFDMG 200
201 GYFIINGSEKVLIAQERSAGNIVQVFKKAAPSPISHVAEIRSALEKGSRF 250
251 ISTLQVKLYGREGSSARTIKATLPYIKQDIPIVIIFRALGIIPDGEILEH 300
301 ICYDVNDWQMLEMLKPCVEDGFVIQDRETALDFIGRRGTALGIKKEKRIQ 350
351 YAKDILQKEFLPHITQLEGFESRKAFFLGYMINRLLLCALDRKDQDDRDH 400
401 FGKKRLDLAGPLLAQLFKTLFKKLTKDIFRYMQRTVEEAHDFNMKLAINA 450
451 KTITSGLKYALATGNWGEQKKAMSSRAGVSQVLNRYTYSSTLSHLRRTNT 500
501 PIGRDGKLAKPRQLHNTHWGLVCPAETPEGQACGLVKNLSLMSCISVGTD 550
551 PMPIITFLSEWGMEPLEDYVPHQSPDATRVFVNGVWHGVHRNPARLMETL 600
601 RTLRRKGDINPEVSMIRDIREKELKIFTDAGRVYRPLFIVEDDESLGHKE 650
651 LKVRKGHIAKLMATEYQDIEGGFEDVEEYTWSSLLNEGLVEYIDAEEEES 700
701 ILIAMQPEDLEPAEANEENDLDVDPAKRIRVSHHATTFTHCEIHPSMILG 750
751 VAASIIPFPDHNQSPRNTYQSAMGKQAMGVFLTNYNVRMDTMANILYYPQ 800
801 KPLGTTRAMEYLKFRELPAGQNAIVAIACYSGYNQEDSMIMNQSSIDRGL 850
851 FRSLFFRSYMDQEKKYGMSITETFEKPQRTNTLRMKHGTYDKLDDDGLIA 900
901 PGVRVSGEDVIIGKTTPISPDEEELGQRTAYHSKRDASTPLRSTENGIVD 950
951 QVLVTTNQDGLKFVKVRVRTTKIPQIGDKFASRHGQKGTIGITYRREDMP 1000
1001 FTAEGIVPDLIINPHAIPSRMTVAHLIECLLSKVAALSGNEGDASPFTDI 1050
1051 TVEGISKLLREHGYQSRGFEVMYNGHTGKKLMAQIFFGPTYYQRLRHMVD 1100
1101 DKIHARARGPMQVLTRQPVEGRSRDGGLRFGEMERDCMIAHGAASFLKER 1150
1151 LMEASDAFRVHICGICGLMTVIAKLNHNQFECKGCDNKIDIYQIHIPYAA 1200
1201 KLLFQELMAMNITPRLYTDRSRDF 1224
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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