 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P36440 from www.uniprot.org...
The NucPred score for your sequence is 0.68 (see score help below)
1 MVNNTFITKLPDFLEIQRSSFCWFLLKGLSYELNSLSPIIDVNVKRVKLK 50
51 LYPQEFVLKPGRTTPICAKQNDSTYGVRIFLPAEVIYCDTESKYPTKKNR 100
101 LEDIKEKVFIGQIPLMTSTGSFIVNGCEGYRNQIIRCPGLYYKAEFLNNN 150
151 IVSTVTIIAQRGSWLKFEFDKNGYWVRIDKEKKISIFDFLEGLNINDEEI 200
201 LSGLKSIAPLLKYKKTQEILKRNNDPDLKNLIEKITDPNSYSLGIIGRLN 250
251 LNRRLGLNISTRVHTLTIHDIFGIIDFFLSARSFVPDDIDDLRNRRIRAV 300
301 GELITSQCEIGLNRLERNILERTNFSGSVRILPKTLVNARPIMSAIQEFF 350
351 NSSQLSHYMDQTNLLSETANKRRISALGPGGLNADRVTVAARDIHPTQYG 400
401 RLCPIETPEGQNVGLVSTLASYARINRNGFIQTPYFRVENGKILTQQPLI 450
451 YLTAEQENLKIAPADVKRDQDGYLVDDFIVTRFQSKNFIITPSKLVDFIS 500
501 VSEIQIISVAASLIPFLEHDDANRALMGANMQRQAVPLLYPRKPIVGTGI 550
551 ESQVAFDSRLVNIATKPGIVKYVSSQQIDIKNIEGEKIAYKLIKYRPSNQ 600
601 DTCLNQRPLVWVGQSIKTGQVIADGPGTQSGELALGQNLTVAYMPWQGYN 650
651 YEDAILVSDKLDIQNLFTSIHIEECETEVQQTKTGEQVITSDIPLVSEKN 700
701 CKNLDENGIIKVGKYVYPGDILVGKITPKGEIDQLPEAKLLKAIFGFKTP 750
751 DMRDSSLRVPGGLSGRVLDIKIFKKPKPGKVFGVGSKIRVFIAQISKLQV 800
801 GDKIAGRHGNKGVISRILPHQDMPFLPDGTSVDIILNPLGVPSRMNVGQI 850
851 FECLLGLAGDQLNKRFKILPFDEMYQNEASRILINQKLKDAAKKQNKPWL 900
901 FSAYSPGKILLSDGRTGEKFDNPVLVGRSYILKLAHLVEDKIHARSTGPY 950
951 SLITQQPVGGKSQNGGQRFGEMEVWALEAFGAAYTLQELLTIKSDDMQGR 1000
1001 DDVLNSIVCGQEIPKSSIPESFKVLMRELNALGLDITTYKVMFENETNKN 1050
1051 CLIKNEINLMQTYEEGIKAKIREEEKEREKEREAREMEDPEKIVSKIDAK 1100
1101 QKKKYKKTKKQTEKKK 1116
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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