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

NucPred

Fetching P14417 from www.uniprot.org...

The NucPred score for your sequence is 0.43 (see score help below)

   1  PNVRWEYCNLTQCSDAEGTAVAPPNVTPVPSLEAPSEQAPTEQRPGVQEC    50
  51  YHGNGQSYRGTYFTTVTGRTCQAWSSMTPHSHSRTPENYPNGGLIRNYCR   100
 101  NPDPVAAPYCYTMDPNVRWEYCNLTQCSDAEGIAVTPLTVTPVPSLEAPS   150
 151  KQAPTEQRPGVQECYHGNGQSYRGTYFTTVTGRTCQAWSSMTPHSHSRTP   200
 201  ENYPNGGLIRNYCRNPDPVAAPYCYTMDPNVRWEYCNLTQCSDAEGTAVA   250
 251  PPNVTPVPSLEAPSEQAPTEQRSGVQECYHGNGQSYRGTYFTTVTGRTCQ   300
 301  AWSSMKPHSHSRTPENYPNGGLIRNYCRNPDPVAAPYCYTMDPNVRWEYC   350
 351  NLTQCSDAEGTAVAPPNVTPVPSLEAPSEQAPTEQRLGVQECYHSNGQSY   400
 401  RGTYFTTVTGRTCQAWSSMTPHSHSRTPENYPNAGLVKNYCRNPDPVAAP   450
 451  WCYTTDPSVRWEYCNLTRCSDAEGTAVMPPNIIPVPSLEAFLEQEPTEET   500
 501  PGVQECYYHYGQSYRGTYSTTVTGRTCQAWSSMTPHQHSRTPKNYPNAGL   550
 551  TRNYCRNPDAEIRPWCYTMDPSVRWEYCNLTQCLVTESSVLETLTVVPDP   600
 601  STQASSEEAPTEQSPEVQDCYHGDGQSYRGSFSTTVTGRTCQSWSSMTPH   650
 651  WHQRTTEYYPDGGLTRNYCRNPDAEIRPWCYTMDPSVRWEYCNLTQCPVT   700
 701  ESSVLATSMAVSEQAPMEQSPGVQDCYHGDGQSYRGSFSTTVTGRICQSW   750
 751  SSMTPHWHQRTIEYYPNGGLTKNYCRNPDAEIRPWCYTMDPRVRWEYCNL   800
 801  TQCVVMESSVLATPMVVPVPSREVPSEEAPTENSPGVQDCYQGDGQSYRG   850
 851  TFSTTITGRTCQSWLSMTPHRHRRIPLRYPNAGLTRNYCRNRDAEIRPWC   900
 901  YTMDPSVRWEYCNLTQCPVTESSVLTTPTVVPVPSTEAPSEQAPPEKSPV   950
 951  VQDCYHGDGQSYRGTSSTTVTGRNCQSWSSMIPHWHQRTPENYPNAGLTR  1000
1001  NYCRNPDSGKHPWCYTTDPCVRWEYCNLTQCSETESGVLETPTVVPVPSM  1050
1051  EAHSEAAPTEQTPVVQQCYHGNGQSYRGTFSTTVTGRTCQSWSSMTPHQH  1100
1101  KRTPENHPNDDLTMNYCRNPDADTGPWCFTMDPSVRREYCNLTRCSDTEG  1150
1151  TVVTPPTVIPVPSLEAPSEQASSSFDCGKPQVEPKKCPGSIVGGCVAHPH  1200
1201  SWPWQVSLRTRFGKHFCGGTLISPEWVLTAACCLETFSRPSFYKVILGAH  1250
1251  QEVNLESHVQEIEVSRLFLEPIGADIALLKLSRPAIITDKVIPACLPSPN  1300
1301  YVITAWTECYITGWGETQGTFGAGLLKEAQLHVIENTVCNHYEFLNGRVK  1350
1351  STELCAGHLAGGTDRCQGDNGGPVVCFDKDKYILRGITSWGPGCACPNKP  1400
1401  GVYVRVSSFVTWIEGVMRNN                                1420

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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