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

NucPred

Fetching P80457 from www.uniprot.org...

The NucPred score for your sequence is 0.25 (see score help below)

   1  MTADELVFFVNGKKVVEKNADPETTLLAYLRRKLGLRGTKLGCGEGGCGA    50
  51  CTVMLSKYDRLQDKIIHFSANACLAPICTLHHVAVTTVEGIGSTKTRLHP   100
 101  VQERIAKSHGSQCGFCTPGIVMSMYTLLRNQPEPTVEEIEDAFQGNLCRC   150
 151  TGYRPILQGFRTFAKNGGCCGGNGNNPNCCMNQKKDHTVTLSPSLFNPEE   200
 201  FMPLDPTQEPIFPPELLRLKDVPPKQLRFEGERVTWIQASTLKELLDLKA   250
 251  QHPEAKLVVGNTEIGIEMKFKNQLFPMIICPAWIPELNAVEHGPEGISFG   300
 301  AACALSSVEKTLLEAVAKLPTQKTEVFRGVLEQLRWFAGKQVKSVASLGG   350
 351  NIITASPISDLNPVFMASGTKLTIVSRGTRRTVPMDHTFFPSYRKTLLGP   400
 401  EEILLSIEIPYSREDEFFSAFKQASRREDDIAKVTCGMRVLFQPGSMQVK   450
 451  ELALCYGGMADRTISALKTTQKQLSKFWNEKLLQDVCAGLAEELSLSPDA   500
 501  PGGMIEFRRTLTLSFFFKFYLTVLKKLGKDSKDKCGKLDPTYTSATLLFQ   550
 551  KDPPANIQLFQEVPNGQSKEDTVGRPLPHLAAAMQASGEAVYCDDIPRYE   600
 601  NELFLRLVTSTRAHAKIKSIDVSEAQKVPGFVCFLSADDIPGSNETGLFN   650
 651  DETVFAKDTVTCVGHIIGAVVADTPEHAERAAHVVKVTYEDLPAIITIED   700
 701  AIKNNSFYGSELKIEKGDLKKGFSEADNVVSGELYIGGQDHFYLETHCTI   750
 751  AIPKGEEGEMELFVSTQNAMKTQSFVAKMLGVPVNRILVRVKRMGGGFGG   800
 801  KETRSTLVSVAVALAAYKTGHPVRCMLDRNEDMLITGGRHPFLARYKVGF   850
 851  MKTGTIVALEVDHYSNAGNSRDLSHSIMERALFHMDNCYKIPNIRGTGRL   900
 901  CKTNLSSNTAFRGFGGPQALFIAENWMSEVAVTCGLPAEEVRWKNMYKEG   950
 951  DLTHFNQRLEGFSVPRCWDECLKSSQYYARKSEVDKFNKENCWKKRGLCI  1000
1001  IPTKFGISFTVPFLNQAGALIHVYTDGSVLVSHGGTEMGQGLHTKMVQVA  1050
1051  SKALKIPISKIYISETSTNTVPNSSPTAASVSTDIYGQAVYEACQTILKR  1100
1101  LEPFKKKNPDGSWEDWVMAAYQDRVSLSTTGFYRTPNLGYSFETNSGNAF  1150
1151  HYFTYGVACSEVEIDCLTGDHKNLRTDIVMDVGSSLNPAIDIGQVEGAFV  1200
1201  QGLGLFTLEELHYSPEGSLHTRGPSTYKIPAFGSIPTEFRVSLLRDCPNK  1250
1251  KAIYASKAVGEPPLFLGASVFFAIKDAIRAARAQHTNNNTKELFRLDSPA  1300
1301  TPEKIRNACVDKFTTLCVTGAPGNCKPWSLRV                    1332

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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