 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q5VYK3 from www.uniprot.org...
The NucPred score for your sequence is 0.67 (see score help below)
1 MAAAAASASQDELNQLERVFLRLGHAETDEQLQNIISKFLPPVLLKLSST 50
51 QEGVRKKVMELLVHLNKRIKSRPKIQLPVETLLVQYQDPAAVSFVTNFTI 100
101 IYVKMGYPRLPVEKQCELAPTLLTAMEGKPQPQQDSLMHLLIPTLFHMKY 150
151 PVESSKSASPFNLAEKPKTVQLLLDFMLDVLLMPYGYVLNESQSRQNSSS 200
201 AQGSSSNSGGGSGIPQPPPGMSFYAAKRVIGDNPWTPEQLEQCKLGIVKF 250
251 IEAEQVPELEAVLHLVIASSDTRHSVATAADLELKSKQSLIDWNNPAIIN 300
301 KMYKVYLGDIPLKTKEGAVLKPELKRDPVSTRVKLKIVPHLLRSRQAAET 350
351 FPANIQVVYDGLFGTNTNSKLRTLSLQFVHHICITCPEIKIKPLGPMLLN 400
401 GLTKLINEYKEDPKLLSMAYSAVGKLSSRMPHLFTKDIALVQQLFEALCK 450
451 EEPETRLAIQEALSMMVGAYSTLEGAQRTLMEALVASYLIKPEVQVRQVA 500
501 VKFASTVFPSDHIPSRYLLLLAAGDPREEVHGEAQRVLRCLPGRNRKEST 550
551 SEQMPSFPEMVYYIQEKASHRMKTPVKYMTGTTVLPFNPAAFGEIVLYLR 600
601 MCLAHSAGVVPTSQSLADMQDHAPAIGRYIRTLMSSGQMAPSSSNKSGET 650
651 NPVQIYIGLLQQLLAGVGGLPVMYCLLEAVSVYPEKLATKFVDKTEWIKS 700
701 LMNNSKEEMRELAALFYSVVVSTVSGNELKSMIEQLIKTTKDNHSPEIQH 750
751 GSLLALGFTVGRYLAKKKMRMSEQQDLERNADTLPDQEELIQSATETIGS 800
801 FLDSTSPLLAIAACTALGEIGRNGPLPIPSEGSGFTKLHLVESLLSRIPS 850
851 SKETNKMKERAIQTLGYFPVGDGDFPHQKLLLQGLMDSVEAKQIELQFTI 900
901 GEAITSAAIGTSSVAARDAWQMTEEEYTPPAGAKVNDVVPWVLDVILNKH 950
951 IISPNPHVRQAACIWLLSLVRKLSTHKEVKSHLKEIQSAFVSVLSENDEL 1000
1001 SQDVASKGLGLVYELGNEQDQQELVSTLVETLMTGKRVKHEVSGETVVFQ 1050
1051 GGALGKTPDGQGLSTYKELCSLASDLSQPDLVYKFMNLANHHAMWNSRKG 1100
1101 AAFGFNVIATRAGEQLAPFLPQLVPRLYRYQFDPNLGIRQAMTSIWNALV 1150
1151 TDKSMVDKYLKEILQDLVKNLTSNMWRVRESSCLALNDLLRGRPLDDIID 1200
1201 KLPEIWETLFRVQDDIKESVRKAAELALKTLSKVCVKMCDPAKGAAGQRT 1250
1251 IAALLPCLLDKGMMSTVTEVRALSINTLVKISKSAGAMLKPHAPKLIPAL 1300
1301 LESLSVLEPQVLNYLSLRATEQEKAAMDSARLSAAKSSPMMETINMCLQY 1350
1351 LDVSVLGELVPRLCELIRSGVGLGTKGGCASVIVSLTTQCPQDLTPYSGK 1400
1401 LMSALLSGLTDRNSVIQKSCAFAMGHLVRTSRDSSTEKLLQKLNGWYMEK 1450
1451 EEPIYKTSCALTIHAIGRYSPDVLKNHAKEVLPLAFLGMHEIADEEKSEK 1500
1501 EECNLWTEVWQENVPGSFGGIRLYLQELITITQKALQSQSWKMKAQGAIA 1550
1551 MASIAKQTSSLVPPYLGMILTALLQGLAGRTWAGKEELLKAIACVVTACS 1600
1601 AELEKSVPNQPSTNEILQAVLKECSKENVKYKIVAISCAADILKATKEDR 1650
1651 FQEFSNIVIPLIKKNSLESSGVRTTKNEEENEKEKELQLEYLLGAFESLG 1700
1701 KAWPRNAETQRCYRQELCKLMCERLKLSTWKVQLGVLQSMNAFFQGLMLL 1750
1751 EEEHADPEALAEILLETCKSITYSLENKTYSSVRTEALSVIELLLKKLEE 1800
1801 SKQWECLTSECRVLLIESLATMEPDSRPELQEKAALLKKTLENLE 1845
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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