 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8TAQ2 from www.uniprot.org...
The NucPred score for your sequence is 0.88 (see score help below)
1 MAVRKKDGGPNVKYYEAADTVTQFDNVRLWLGKNYKKYIQAEPPTNKSLS 50
51 SLVVQLLQFQEEVFGKHVSNAPLTKLPIKCFLDFKAGGSLCHILAAAYKF 100
101 KSDQGWRRYDFQNPSRMDRNVEMFMTIEKSLVQNNCLSRPNIFLCPEIEP 150
151 KLLGKLKDIIKRHQGTVTEDKNNASHVVYPVPGNLEEEEWVRPVMKRDKQ 200
201 VLLHWGYYPDSYDTWIPASEIEASVEDAPTPEKPRKVHAKWILDTDTFNE 250
251 WMNEEDYEVNDDKNPVSRRKKISAKTLTDEVNSPDSDRRDKKGGNYKKRK 300
301 RSPSPSPTPEAKKKNAKKGPSTPYTKSKRGHREEEQEDLTKDMDEPSPVP 350
351 NVEEVTLPKTVNTKKDSESAPVKGGTMTDLDEQEDESMETTGKDEDENST 400
401 GNKGEQTKNPDLHEDNVTEQTHHIIIPSYAAWFDYNSVHAIERRALPEFF 450
451 NGKNKSKTPEIYLAYRNFMIDTYRLNPQEYLTSTACRRNLAGDVCAIMRV 500
501 HAFLEQWGLINYQVDAESRPTPMGPPPTSHFHVLADTPSGLVPLQPKTPQ 550
551 QTSASQQMLNFPDKGKEKPTDMQNFGLRTDMYTKKNVPSKSKAAASATRE 600
601 WTEQETLLLLEALEMYKDDWNKVSEHVGSRTQDECILHFLRLPIEDPYLE 650
651 DSEASLGPLAYQPIPFSQSGNPVMSTVAFLASVVDPRVASAAAKSALEEF 700
701 SKMKEEVPTALVEAHVRKVEEAAKVTGKADPAFGLESSGIAGTTSDEPER 750
751 IEESGNDEARVEGQATDEKKEPKEPREGGGAIEEEAKEKTSEAPKKDEEK 800
801 GKEGDSEKESEKSDGDPIVDPEKEKEPKEGQEEVLKEVVESEGERKTKVE 850
851 RDIGEGNLSTAAAAALAAAAVKAKHLAAVEERKIKSLVALLVETQMKKLE 900
901 IKLRHFEELETIMDREREALEYQRQQLLADRQAFHMEQLKYAEMRARQQH 950
951 FQQMHQQQQQPPPALPPGSQPIPPTGAAGPPAVHGLAVAPASVVPAPAGS 1000
1001 GAPPGSLGPSEQIGQAGSTAGPQQQQPAGAPQPGAVPPGVPPPGPHGPSP 1050
1051 FPNQQTPPSMMPGAVPGSGHPGVAGNAPLGLPFGMPPPPPPPAPSIIPFG 1100
1101 SLADSISINLPAPPNLHGHHHHLPFAPGTLPPPNLPVSMANPLHPNLPAT 1150
1151 TTMPSSLPLGPGLGSAAAQSPAIVAAVQGNLLPSASPLPDPGTPLPPDPT 1200
1201 APSPGTVTPVPPPQ 1214
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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