 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q21534 from www.uniprot.org...
The NucPred score for your sequence is 0.74 (see score help below)
1 MLHYLLSVLLLIFENILELCMCITLVILIYYFWPSKQLEDATLQYFPDTT 50
51 QNSSEVFIDPPERNPIFYPISPLRHKKRSSKEEMTPDKKRDSSEKISKQP 100
101 PRELFEPNEQEQVPSHIKPEIFFVLKALEGLELPTTWQLDPKDVETLSID 150
151 TGSVVLSPGRANDVIVVVISGELGIFTNVSLGDKRYDCNIKTLRSGESYF 200
201 SQTSIIEILMNEKPNNKYIHLKALTSCRVATYHLTSFHTSFIANPQQWIR 250
251 TIQVVMTRLQQCTLITCNMYLGIGGKCLNAKRKLPDSGKFKDFNKLTEAE 300
301 QLNKGVEAIAQAMGIPDQSDKLREKVRKYECQAGTVVTEENSFEIDMIFV 350
351 VFGKLRLKRGDLEHDDTGTSLTFDVYPGDMLPSMQILTNEPAMCSAKALE 400
401 KTIYFKICRDEYIQFLFAHPVIYLRLAFHALQFISPFARVFDMAVHWHRI 450
451 ETGQALFRQGDKSDSMHIVMGGRLRAVDSTKIIEEYGRLDLIGITDMAEK 500
501 RPRRNTVMAVRFSHIVCIPENLLSFVKIRYPQVGNKLLKLISKCWKAPTP 550
551 ETMSHVETTRNQNLRTIAIVPASRRVPLTEFTCELYNQLSKHVKTLRLSS 600
601 SVVENYFESEVITKKADYGLMHWLNVQEIAYSLVLYQCDFHKTNWTRRCL 650
651 RMADAILMVALGTESKEEQVLAEALLSCNEKGVRQSKELVFLWPIDTPTP 700
701 SGTAAWIKESYYSGYHHLRAPNRLFSFPLKTREKKIVEYYETTVYGEISY 750
751 QSDFSRLARILTGNAIGIVFGGGGARGAAHAGALRALIEKKVQIDMVGGT 800
801 SIGALFGSLYATTPDIRAVGRMKDFFTDRLRNNILDVVRDLTWPYCGILT 850
851 GHRFNLCVQRMLNDVNIEDCWVSFFCITTDLTSSSMRIHRNGIMWPVVRS 900
901 SMSIAGYVPPICDPQDGHLLLDGAYVNNLPADIMRSLGANVVIAIDVGMS 950
951 DDNTNLRNYGFSISGTWCLFKRWWPFGEELRVLNMNEVQNRLAYVCCVNQ 1000
1001 MEIVKNAQYCYYVKLPIESFGIFDFSKFDQAAQIGYDITKQKMEEFFEDS 1050
1051 VATRRKLLGCARNVRQTPQKSKNDNILSFVNMPVLPKPPSDIKSD 1095
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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