 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9UT00 from www.uniprot.org...
The NucPred score for your sequence is 0.31 (see score help below)
1 MSSQAEPSKGASNADPNEKVEKMHLPTDTAGGGVKVKVKEQEASPSDKNN 50
51 LNPQSAGVSEVQVQDDTGARGSGARDLKVPKQMQAPKSSEEKSDVDGVPT 100
101 RPVSERELRKRDAMQFIQRHQKVRNILAQYCPWLTDERLQLCIELKILFM 150
151 QHFQDSRLVLYTAVMSFLFGYLRFGFLSLFIIMAVCIQYYRICDRRVKVN 200
201 FKDDYTRYLSTRKLENDSETVTWLNTFLQQFWYIFEPSLSERITEITDQI 250
251 LSENVPSFIDSMALSEFTLGTKSPRMGFIRSYPKTEEDTVMMDLRLAFSP 300
301 NDISDLTGREIAACIKPKIALDLKIGKSIASAKMPVLIEDLSFTGNLRVK 350
351 VKLIDKYPYAKTVGLTFTEKPVFSYILKPLGGDKFGFDIGNIPGLTTFIT 400
401 EQIHNTLGPMMYSPNVYELDIESMMGAAGLNTALGAVEFKLRKGDGFKDG 450
451 LGGAVDPYVVIKNSADRVIGKSKVAHNTGSPVFNETFYSVLNSFSENLNL 500
501 EVYDFNDIRSDKLLGSAVLPLATLEAMPVTNDAFVELTLKGKTVGRLNYD 550
551 MKFHAVVPDSGEEITKVDGPGVLQFTVHQCKELSNDPSKRPTAYAKLIIN 600
601 NKEVYTTRKIKKNNNPSWEESFGTLLPEGKNATLGVQIFTEESEHPFGTA 650
651 NVSLQDLFAATKTGLLWFPLQHAPSGRVRMSVMWKPAQLNNDSISSMALA 700
701 TPIGAIRIHLRSANNLHSKIPGKKCDSYARIMSHNTKQFRTVVIASNVNP 750
751 FWDEYMYAPVITKHDIFFLQVMNYNSSGEDKLIGQTPINISNFINQGENG 800
801 ALMEYHDPRELTVPLSSTRGIKGNATITFKCDFFPSAVTTSLSPDVTPAP 850
851 KASSTVATDKVNIEVLPESQKTPTAVDNTSTSRGSTSVKTSKPKKISELL 900
901 MPSEAVNAALDFESGFMGFDIISYKIAKPAQELAIFLDDLPHHIFLSSAL 950
951 NVTGGATLHEYGNTFIRQLEYSQCTFKLLDGDKEVGSKTMLSRDLISKGA 1000
1001 TKPLEIAFPDGASILVAFRLTPVPVKLEEVEMYENMGEMTVDVIKATDLP 1050
1051 AADSNGKSDPFVVFELQGEEVYRTKTHKRTLNPTFNESFEVELPCKQTCN 1100
1101 FVANVFDWDFGNKDDHLGSCVIDCKLLQQQQQTNYEIPLDSKQGVLYLRI 1150
1151 TLSPKWVLRSKRAGNSSLVEGILGQTASIVGMPLKGISTVGNVAVDGVAS 1200
1201 VANLTNKMRKGISRGFKGIHHEKAK 1225
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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