 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9DDT5 from www.uniprot.org...
The NucPred score for your sequence is 0.61 (see score help below)
1 MSDSEDSDFSDNQSERSSEAEEVEENEEEEEQGSVAGSDKAEEEGEDLED 50
51 EEEYDEEEEEDDDRPRKKARHGGFILDEADVDDEYEDEDPWEDGAEDILE 100
101 KEEAEVSNLDHVVLDEDHSGSRRLQNLWRDSREEALGEYYMRKYAKSSGG 150
151 EHFYGGSEDLSDDITQQQLLPGVKDPNLWTVKCKIGEERATAISLMRKFV 200
201 AYQCTDTPLQIKSVVAPEHVKGYIYVEAYKQTHVKAAIEGVGNLRMGFWN 250
251 QQMVPIKEMTDVLKVVKEVTNLKPKSWVRLKRGLYKDDIAQVDYVEPSQN 300
301 TISLKMIPRIDLDRIKARMSMKDWFAKRKKFKRPPQRLFDAEKIRSLGGE 350
351 VSHDGDFMIFEANRYSRKGFLFKSFAMSAVITEGVKPTLSELEKFEDQPE 400
401 GIDLEVVTETTGKEREHNLQAGDNVEVCEGELINLQGKILSVDGNKITIM 450
451 PKHEDLKDPLEFPAHELRKYFRMGDHVKVIAGRYEGDTGLIVRVEENFVI 500
501 LFSDLTMHELKVLPRDLQLCSETASGVDAGGQHEWGELVQLDPQTVGVIV 550
551 RLERETFQVLNMHGKVLTVRHQAVNRRKDNRFAVALDSEQNNIHVKDIVK 600
601 VIDGPHSGREGEIRHIFRGFAFLHCKKLVENGGMFVCKARHLVLAGGSKP 650
651 RDVTNFTVGGFAPMSPRISSPMHPGGGGQPQRGGGGGGGGGMGRGRGRRD 700
701 NDLIGQTVRISQGPYKGYIGVVKDATESTARVELHSTCQTISVDRQRLTT 750
751 VGGKERQGRSSTHLRTPMYGSQTPIYGTGSRTPMYGSQTPLHDGSRTPHY 800
801 GSQTPLHDGSRTPGQSGAWDPNNPNTPSRPDDEYEFAYDDEPSPSPQGYG 850
851 GTPNPQTPGYPEVPSPQVNPQYNPQTPGTPAMYNTDQYSPYAAPSPQGSY 900
901 QPSPSPQSYHQVAPSPVGYQNTHSPASYHPTPSPMAYQASPSPSPVGYSP 950
951 MTPGAPSPGGYNPHTPGSNIDQASNDWVTTDIMVRVKDTFLDGGVINQTG 1000
1001 IIRSVTGGMCSVFLQDTEKVVSISSEHLEPVTPTKNNKVKVILGEDREAT 1050
1051 GVLLSIDGEDGIVRMELDEQLKILNLRFLGKLEV 1084
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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