 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O55201 from www.uniprot.org...
The NucPred score for your sequence is 0.63 (see score help below)
1 MSDSEDSNFSEEEDSERSSEAEEAEVEEDQRSAAGSEKEEEPEEEEEEEE 50
51 EYDEEEEEEDDDRPPKKPRHGGFILDEADVDDEYEDEDQWEDGAEDILEK 100
101 EEIEASNIDNVVLDEDRSGARRLQNLWRDQREEELGEYYMKKYAKSSVGE 150
151 TVYGGSDELSDDITQQQLLPGVKDPNLWTVKCKIGEERATAISLMRKFIA 200
201 YQFTDTPLQIKSVVAPEHVKGYIYVEAYKQTHVKQAIEGVGNLRLGYWNQ 250
251 QMVPIKEMTDVLKVVKEVANLKPKSWVRLKRGIYKDDIAQVDYVEPSQNT 300
301 ISLKMIPRIDYDRIKARMSLKDWFAKRKKFKRPPQRLFDAEKIRSLGGDV 350
351 ASDGDFLIFEGNRYSRKGFLFKSFAMSAVITEGVKPTLSELEKFEDQPEG 400
401 IDLEVVTESTGKEREHNFQPGDNVEVCEGELINLQGKVLSVDGNKITIMP 450
451 KHEDLKDMLEFPAQELRKYFKMGDHVKVIAGRFEGDTGLIVRVEENFVIL 500
501 FSDLTMHELKVLPRDLQLCSETASGVDVGGQHEWGELVQLDPRTVGVIVR 550
551 LERETFQVLNMHGKVVTVRHQAVTQKKDNRFAVALDSDQNNIHVKDIVKV 600
601 IDGPHSGREGEIRHLYRSFAFLHCKKLVENGGMFVCKARHLVLAGGSKPR 650
651 DVTNLTVGGFTPMSPRISSPMHPSAEGQHGGFGSPGGMSRGRGRRDNELI 700
701 GQTVRISQGPYKGYIGVVKDATESTARVELHSTCQTISVDRQRLTTVDSQ 750
751 RPGGMTSTYGRTPMYGSQTPMYGSGSRTPMYGSQTPLQDGSRTPHYGSQT 800
801 PLHDGSRTPAQSGAWDPNNPNTPSRAEEEYEYAFDDEPTPSPQAYGGTPN 850
851 PQTPGYPDPSSPQVNPQYNPQTPGTPAMYNTDQFSPYAAPSPQGSYQPSP 900
901 SPQSYHQVAPSPAGYQNTHSPASYHPTPSPMAYQASPSPSPVGYSPMTPG 950
951 APSPGGYNPHTPGSGIEQNSSDWVTTDIQVKVRDTYLDTQIVGQTGVIRS 1000
1001 VTGGMCSVYLKDSEKVVSISSEHLEPITPTKNNKVKVILGEDREATGVLL 1050
1051 SIDGEDGIIRMDLEDQQIKILNLRFLGKLLEA 1082
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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