SBC logo Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden.

NucPred

Fetching Q3TUF7 from www.uniprot.org...

The NucPred score for your sequence is 0.67 (see score help below)

   1  MSGIKRTIKETDPDYEDVSVALPNKRHKAIESSARDAAVQKIETIIKEQF    50
  51  ALEMKNKEHEIDVIDQRLIEARRMMDKLRACIVANYYASAGLLKVSEGLK   100
 101  TFDPMAFNHPAIKKFLESPSRSSSPTNQRSETPSANHSESDSLSQHNDFL   150
 151  SDKDNNSNVDVEERPPSTGEQRPSRKAGRDTSSISGSHKRELRNADLTGD   200
 201  ETSRLFVKKTIVVGNVSKYIPPDKREENDQSTHKWMVYVRGSRREPSINH   250
 251  FVKKVWFFLHPSYKPNDLVEVREPPFHLTRRGWGEFPVRVQVHFKDSQNK   300
 301  RIDIIHNLKLDRTYTGLQTLGAETVVDVELHRHSLGEDSVYPQSSESDVC   350
 351  DAPPPTLTLPAAVKASAVAQSPEPAAAAPVGEGFPETTEAERHSTFYSLP   400
 401  SSLERTPTKVTTAQKVTFSSHGNSAFQPIASSCKIVPQSQVPNPESPGKS   450
 451  FQPITMSCKIVSGSPISTPSPSPLPRTPTSTPVHLKQGTASSGVSNPHVI   500
 501  VDKPGQVIGASTPSTGSPTSKLPVASQASQGTGSPIPKIHGSSFLTSTVK   550
 551  QEESLFASMPPLCPIGSHPKVQSPKAVTGGLGAFTKVIIKQEPGEAPHVS   600
 601  TTGAASQSAFPQYVTVKGGHMIAVSPQKQVISAGEGTTQSPKIAPSKVVG   650
 651  VPVGSALPSTVKQAVAISSGQILVAKASSSVTKAVGPKQVVTQGVAKAIV   700
 701  SGGGGTIVAQPVQTLTKTQVTAAGPQKSGSQGSVMATLQLPATNLANLAN   750
 751  LPPGTKLYLTTNSKNPSGKGKLLLIPQGAILRATNNANLQSGSAAAGGSG   800
 801  SSGAGGGSGGGGGSGAGGTPSTSGPGGGPQHLTYTSYILKQTPQGTFLVG   850
 851  QPSPQTPGKQLTTASVVQGTLGVSSSSAQGQQTLKVISGQKTTLFTQAAT   900
 901  AGQASLLKLPDNTLKSVPAAPQLAKPGTTMLRVAGGVITAAPSPAVAFSA   950
 951  NGAVHQSEGSTPVSSSVGSIIKTPGQPQVCVSQATMATCKGPAAVAGTAA  1000
1001  SLVSAPSSISGKATVSGLLKVHSAQSSPQQAVLTIPSQLKPLSINTSGGV  1050
1051  QTVLMPVNKVVQSFSTSKLPTTVLPISVPNQAAPSSAPVAIAKVKTEPET  1100
1101  PGPNCISQENQVAVKTEESSELSNYVIKVDHLETIQQLLTAVVKKIPLIT  1150
1151  AKGDDASCFSAKSLEQYYGWNIGKRRAAEWQRAMTVRKVLQEILEKNPRF  1200
1201  HHLTPLKTKHIAHWCRCHGYTPPDPESLRHDGDSIEDVLTQIDSEPECLS  1250
1251  SFSTADDLCRKLEDLQQFQKREPENEEEVDILSLSEPLKTNIKKEQEEKQ  1300
1301  EEMRFYLPPTPGSGFVGDITQKIGITLQPVALHRNMYASVVEDMILKATE  1350
1351  QLVSDILRQALAVGYQTASPNRIPKEITVSNIHQAICNIPFLDFLTNKHM  1400
1401  GRLNEDQ                                             1407

Positively and negatively influencing subsequences are coloured according to the following scale:

(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)

with NucPred



If you find NucPred useful, please cite this paper:
NucPred - Predicting Nuclear Localization of Proteins. Brameier M, Krings A, Maccallum RM. Bioinformatics, 2007. PubMed id: 17332022
The authors also look forward to your comments and suggestions.

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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