 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q64632 from www.uniprot.org...
The NucPred score for your sequence is 0.51 (see score help below)
1 MAGLCSSPWVKLLLAVVLSAGLPGNMANRCKKAQVKSCTECIRVDKSCAY 50
51 CTDELFKERRCNTQADVLAAGCRGESVLVMESSLEITENIQIDTSLHRSQ 100
101 VSPQGLQVRLRPGEERNFVFKVFEPLESPVDLYILMDFSNSMSDDLDNLK 150
151 QMGQNLAKILRQLTSDYTIGFGKFVDKVSVPQTDMRPEKLKEPWPNSDPP 200
201 FSFKNVISLTENVEEFWDKLQGERISGNLDAPEGGFDAILQTAVCTRDIG 250
251 WRADSTHLLVFSTESAFHYEADGANVLAGIMNRNDEKCHLDATGAYTQYK 300
301 TQDYPSVPTLVRLLAKHNIIPIFAVTNYSYSYYEKLHKYFPVSSLGVLQE 350
351 DSSNIVELLEEAFYRIRSNLDIRALDSPRGLRTEVTSDTLQKTETGSFHI 400
401 KRGEVGTYNVHLRAVEDIDGTHVCQLAKEDQRGNIHLKPSFSDGLRMDAS 450
451 VICDMCACELQKEVQSARCHYRGDFMCGHCVCNEGWSGKTCNCSTGSLSD 500
501 TQPCLREGEDKPCSGHGECQCGRCVCYGEGRYEGHFCEYDNFQCPRTSGF 550
551 LCNDRGRCSMGECVCEPGWTGRSCDCPLSNATCIDSNGGICNGLGFCECG 600
601 RCHCNQRSSLYTDTTCEINYSAIRLGLCEDLRSCVQCQAWGTGEKKGRTC 650
651 EECNFKVKMVDELKKAEEVVEYCSFRDEDDDCTYSYTVEGDGSPGPNSTV 700
701 LVHKKKDCLPAPSWWLIPLLIFLLLLLVLLLLLCWKYCACCKACLGLLPC 750
751 CNQGHMVGFKEDHYMLRENLMASDHLDTPMLRSGNLKGRDTVRWKITNNV 800
801 QRPGFATHAASISPTELVPYGLSLRLGRLCTENLMKPGTRECDQLRQEVE 850
851 ENLNEVYRQVNGVHKLQQTKFRQQPNAGKKQDHTIVDTVLLAPRSAKQSL 900
901 LKLTEKQVEQGSFHELKVAPGYYTLTAEQDARGMVEFQEGVELVDVRVPL 950
951 FIRPEDDDEKQLLVEAIDVPVGTATLGRRLVNITIIKEQASGIVSFEQPE 1000
1001 YSVSRGDQVARIPVIRHILDNGKSQVSYSTQDNTAHGHRDYVPVEGELLF 1050
1051 YPGETWKELQVKLLELQEVDSLLRGRQVRRFQVQLSNPKFGARLGQPNTA 1100
1101 TVIIGEQDETDRSLINEISASPPLPRGDLGAPQNPNAKAAGSRKIHFNWL 1150
1151 PPPGKPMGYRVKYWVQGDSESEAHLLDSKVPSVELTNLYPYCDYEMKVCA 1200
1201 YGAHGEGPYSSLVSCRTHQEVPSEPGRLAFNVVSSTVTQLSWAEPAETNG 1250
1251 EITAYEVCYGLVNEDNRPIGPMKKVLVDNPKNRMLLIENLRESQPYRYTV 1300
1301 KARNGAGWGPEREAIINLATQPKRPMSIPIIPDIPIVDAQGGEDYENFLM 1350
1351 YSDDVLRSPASSQRPSVSDDTEHLVNGRMDFAYPGSANSLHRMTAANVAY 1400
1401 GTHLSPHQTHRMLSTSSTLTRDYHSLTRTDHSQSGTLPRDYSTLTSLSSQ 1450
1451 GLPPIWEDGRSRLPLSWTLGSWSRAQMKGVPASRGSPDSIILAGQSAAPS 1500
1501 WGTDSRGAMGVPDTPTRLVFSALGPTSLKVSWQEPQCDRALLGYSVEYQL 1550
1551 LNGGEMHRLNIPNPGQTSVVVEDLLPNHSYVFRVRAQSQEGWGREREGVI 1600
1601 TIESQVHPQSPLCPLPGSAFTLSTPSAPGPLVFTALSPDSLQLSWERPRR 1650
1651 PNGDILGYLVTCEMAQGGGPARTFRVDGDNPESRLTVPGLSENVPYKFKV 1700
1701 QARTTEGFGPEREGIITIESQDGGPFPQLGSHSGLFQNPLQSEYSTVTST 1750
1751 HSTTTTEPFLIDGLTLGTQRLEAGGSLTRHVTQEFVSRTLTTSGSLSTHM 1800
1801 DQQFFQT 1807
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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