 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P00519 from www.uniprot.org...
The NucPred score for your sequence is 0.80 (see score help below)
1 MLEICLKLVGCKSKKGLSSSSSCYLEEALQRPVASDFEPQGLSEAARWNS 50
51 KENLLAGPSENDPNLFVALYDFVASGDNTLSITKGEKLRVLGYNHNGEWC 100
101 EAQTKNGQGWVPSNYITPVNSLEKHSWYHGPVSRNAAEYLLSSGINGSFL 150
151 VRESESSPGQRSISLRYEGRVYHYRINTASDGKLYVSSESRFNTLAELVH 200
201 HHSTVADGLITTLHYPAPKRNKPTVYGVSPNYDKWEMERTDITMKHKLGG 250
251 GQYGEVYEGVWKKYSLTVAVKTLKEDTMEVEEFLKEAAVMKEIKHPNLVQ 300
301 LLGVCTREPPFYIITEFMTYGNLLDYLRECNRQEVNAVVLLYMATQISSA 350
351 MEYLEKKNFIHRDLAARNCLVGENHLVKVADFGLSRLMTGDTYTAHAGAK 400
401 FPIKWTAPESLAYNKFSIKSDVWAFGVLLWEIATYGMSPYPGIDLSQVYE 450
451 LLEKDYRMERPEGCPEKVYELMRACWQWNPSDRPSFAEIHQAFETMFQES 500
501 SISDEVEKELGKQGVRGAVSTLLQAPELPTKTRTSRRAAEHRDTTDVPEM 550
551 PHSKGQGESDPLDHEPAVSPLLPRKERGPPEGGLNEDERLLPKDKKTNLF 600
601 SALIKKKKKTAPTPPKRSSSFREMDGQPERRGAGEEEGRDISNGALAFTP 650
651 LDTADPAKSPKPSNGAGVPNGALRESGGSGFRSPHLWKKSSTLTSSRLAT 700
701 GEEEGGGSSSKRFLRSCSASCVPHGAKDTEWRSVTLPRDLQSTGRQFDSS 750
751 TFGGHKSEKPALPRKRAGENRSDQVTRGTVTPPPRLVKKNEEAADEVFKD 800
801 IMESSPGSSPPNLTPKPLRRQVTVAPASGLPHKEEAGKGSALGTPAAAEP 850
851 VTPTSKAGSGAPGGTSKGPAEESRVRRHKHSSESPGRDKGKLSRLKPAPP 900
901 PPPAASAGKAGGKPSQSPSQEAAGEAVLGAKTKATSLVDAVNSDAAKPSQ 950
951 PGEGLKKPVLPATPKPQSAKPSGTPISPAPVPSTLPSASSALAGDQPSST 1000
1001 AFIPLISTRVSLRKTRQPPERIASGAITKGVVLDSTEALCLAISRNSEQM 1050
1051 ASHSAVLEAGKNLYTFCVSYVDSIQQMRNKFAFREAINKLENNLRELQIC 1100
1101 PATAGSGPAATQDFSKLLSSVKEISDIVQR 1130
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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