 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P09436 from www.uniprot.org...
The NucPred score for your sequence is 0.18 (see score help below)
1 MSESNAHFSFPKEEEKVLSLWDEIDAFHTSLELTKDKPEFSFFDGPPFAT 50
51 GTPHYGHILASTIKDIVPRYATMTGHHVERRFGWDTHGVPIEHIIDKKLG 100
101 ITGKDDVFKYGLENYNNECRSIVMTYASDWRKTIGRLGRWIDFDNDYKTM 150
151 YPSFMESTWWAFKQLHEKGQVYRGFKVMPYSTGLTTPLSNFEAQQNYKDV 200
201 NDPAVTIGFNVIGQEKTQLVAWTTTPWTLPSNLSLCVNADFEYVKIYDET 250
251 RDRYFILLESLIKTLYKKPKNEKYKIVEKIKGSDLVGLKYEPLFPYFAEQ 300
301 FHETAFRVISDDYVTSDSGTGIVHNAPAFGEEDNAACLKNGVISEDSVLP 350
351 NAIDDLGRFTKDVPDFEGVYVKDADKLIIKYLTNTGNLLLASQIRHSYPF 400
401 CWRSDTPLLYRSVPAWFVRVKNIVPQMLDSVMKSHWVPNTIKEKRFANWI 450
451 ANARDWNVSRNRYWGTPIPLWVSDDFEEVVCVGSIKELEELTGVRNITDL 500
501 HRDVIDKLTIPSKQGKGDLKRIEEVFDCWFESGSMPYASQHYPFENTEKF 550
551 DERVPANFISEGLDQTRGWFYTLAVLGTHLFGSVPYKNVIVSGIVLAADG 600
601 RKMSKSLKNYPDPSIVLNKYGADALRLYLINSPVLKAESLKFKEEGVKEV 650
651 VSKVLLPWWNSFKFLDGQIALLKKMSNIDFQYDDSVKSDNVMDRWILASM 700
701 QSLVQFIHEEMGQYKLYTVVPKLLNFIDELTNWYIRFNRRRLKGENGVED 750
751 CLKALNSLFDALFTFVRAMAPFTPFLSESIYLRLKEYIPEAVLAKYGKDG 800
801 RSVHFLSYPVVKKEYFDEAIETAVSRMQSVIDLGRNIREKKTISLKTPLK 850
851 TLVILHSDESYLKDVEALKNYIIEELNVRDVVITSDEAKYGVEYKAVADW 900
901 PVLGKKLKKDAKKVKDALPSVTSEQVREYLESGKLEVAGIELVKGDLNAI 950
951 RGLPESAVQAGQETRTDQDVLIIMDTNIYSELKSEGLARELVNRIQKLRK 1000
1001 KCGLEATDDVLVEYELVKDTIDFEAIVKEHFDMLSKTCRSDIAKYDGSKT 1050
1051 DPIGDEEQSINDTIFKLKVFKL 1072
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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