 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q80X19 from www.uniprot.org...
The NucPred score for your sequence is 0.16 (see score help below)
1 MMIWQCKMRDWLILAFLAAACFCTIVRGQVAPPTRLRYNVISHDSIQISW 50
51 KAPRGKFGGYKLLVAPASGGKTNQMNLQNTATKAIIQGLLPEQNYTVQLI 100
101 AYYKDKESKPAQGQFRIKDLEKRKDPTKPKVKVVDKGNGSKPTSPEEVKF 150
151 FCETPAIADIVILVDGSWSIGRFNFRLVRNFLENLVTAFNVGSEKTRIGL 200
201 AQYSGDPRIEWHLNAFNTKDEVIDAVRSLPYKGGNTLTGLALNFIFENSF 250
251 KPEAGSRSGVSKIGILITDGKSQDDIIPPSRNLRESGVELFAIGVKNADL 300
301 SELQEIASEPDSTHVYNVAEFDLMHTVVESLTRTVCSRVEEQDKEIKASA 350
351 LATIGPPTELITSEVTARSFMVNWTQSPGKVEKYRVVYYPTRGGKPEEVV 400
401 VDGSVSSTVLKNLMSSTEYQIAVFAVSAHTASEGLRGAETTLALPMASDL 450
451 ELYDVTENSMRVRWDAVPGATGYLILYAPLTEGLAGDEKEMKIGETHTDI 500
501 ELSGLFPNTEYTVTVYAMFGEEASDPATGQETTLPLTPPRNLRISNVGSN 550
551 SARLTWDPASGKISGYRIVYTSADGTEINEVEVDPITTFPLKGLTPLTEY 600
601 SIAIFSIYEEGQSLPLVGEFTTEEVPAQQYLEIDEVKTDSFRVTWHPLSA 650
651 EEGQHKLMWIPVYGGKTQEVDLKEEQDSYVIEGLDPGTEYEVSLLAVLDD 700
701 GSESEVVTAVGTTLDDFWTEAPTAIEPTSPVTSVLQTGIRNLVVDDETAT 750
751 SLRVSWDISDSNVEQFRVTYLKAQGDPMEEVVGTVMVPGVQNSLLLKALL 800
801 PDTEYKVTVTPVYTVGEGVSVSAPGKTLPSSGPQNLRVSEEWYNRVRITW 850
851 DPPSGPVKGYRIVYKPVSVPGQTLETFVGADINTIVMTNLLSGMDYNVKI 900
901 FASQASGFSDALTGLVQTLFLGVTDLQANQVEMTSLCARWQIHRHATAYR 950
951 IVLESLQDTQAQESTVGGGVNRHCFYGLQPDSEYKISVYTKLQELEGPSV 1000
1001 SIMQKTQSLPTEPPTFPPTIPPAKEVCKAAKADLVFMVDGSWSIGDDNFN 1050
1051 KIINFLYSTVGALDKIGADGTQVAMVQFTDDPRTEFKLDSYKTKETLLDA 1100
1101 IRHISYKGGNTKTGKAIKHVRDTLFTSDSGTRRGIPKVIVVITDGRSQDD 1150
1151 VNKISREMQADGFNIFAIGVADADYSELVQIGSKPSSRHVFFVDDFDAFK 1200
1201 KIEDELITFVCETASATCPMVHKDGVDLAGFKMMEMFGLVEKDFSAVEGV 1250
1251 SMEPGTFNLFPCYQIHKDALVSQPTKYLHPEGLPSDYTMSFLFRILPDTP 1300
1301 QEPFALWEILNKNSEPLVGIILDNGGKTLTYFNYDYTGDFQTVTFEGPDI 1350
1351 RKMFYGSFHKLHVVVSKTLAKVVVDCKEVGQKAINASANITSDGVEVLGR 1400
1401 MVRSRGPNGNSAPFQLQMFDIVCSTSWASKDRCCELPGLRDEESCPDLPR 1450
1451 SCSCSETNEVALGPAGPPGGPGLRGPKGQQGEQGPKGPEGPRGETGPAGP 1500
1501 QGPPGPQGPSGLSIQGMPGMPGDKGDKGDAGLPGPQGVPGGVGSPGRDGS 1550
1551 PGQRGFPGKDGSSGPPGPPGPIGIPGAPGVPGITGSMGPQGALGPPGVPG 1600
1601 AKGERGERGDLQSQAMVRAVARQVCEQLIQSHMARYTAILNQIPSQSSSI 1650
1651 RTIQGPPGEPGRPGSPGTPGEQGPPGTPGFPGNAGVPGTPGERGLTGVKG 1700
1701 EKGNPGIGTQGPRGPPGPAGPSGESRPGSPGPPGSPGPRGPPGHLGVPGP 1750
1751 QGPSGQPGYCDPSSCSAYGVGVSHPDQPEFTPVQDEQEAMDLWSAGI 1797
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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