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

NucPred

Fetching O97827 from www.uniprot.org...

The NucPred score for your sequence is 0.72 (see score help below)

   1  MWPSQLLVFMMLLAPIIHGGKHSERHPALASPLRHAERGPGGALPPRHLL    50
  51  QQPAAERATAHRGPGPRGATRGVRGPGAHGAQISAQAFSRAPIPMAVVRR   100
 101  ELSCESYPIELRCPGTDVIMIESANYGRTDDKICDSDPAQMENIRCYLPD   150
 151  AYKIMSQRCNNRTQCAVVAGPDVFPDPCPGTYKYLEVQYECVPYKVEQKV   200
 201  FLCPGLLKGVYQSEHLFESDHQSGAWCKDPLQASDKIYYMPWTPYRTDTL   250
 251  TEYSSKDDFIAGRPTTTYKLPHRVDGTGFVVYDGALFFNKERTRNIVKFD   300
 301  LRTRIKSGEAIIANANYHDTSPYRWGGKSDIDLAVDENGLWVIYATEQNN   350
 351  GKIVISQLNPYTLRIEGTWDTAYDKRSASNAFMICGILYVVKSVYEDDDN   400
 401  EATGNKIDYIYNTDQSKDSLVDVPFPNSYQYIAAVDYNPRDNLLYVWNNY   450
 451  HVVKYSLDFGPLDSRSGQAHHGQVSYISPPIHLDSDLERPPVREISTTGP   500
 501  LGTGSTTTSTTLRTTTWSPGRSTTPSVSGRRNRSTSTPSPAIEVLNDITT   550
 551  HVPSASPQIPALEESCEAVEAREIMWFKTRQGQMAKQPCPAGTIGVSTYL   600
 601  CLAPDGIWDPQGPDLSNCSSPWVNHITQKLKSGETAANIARELAEQTRNH   650
 651  LNAGDITYSVRAMDQLVGLLDVQLRNLTPGGKDSAARSLNKLQKRERSCR   700
 701  AYVQAMVETVNNLLQPQALNAWRDLTTSDQLRAATMLLDTVEESAFVLAD   750
 751  NLLKTDIVRENTDNIQLEVARLSTEGNLEDLKFPENTGHGSTIQLSANTL   800
 801  KQNGRNGEIRVAFVLYNNLGPYLSTENASMKLGTEAMSTNHSVIVNSPVI   850
 851  TAAINKEFSNKVYLADPVVFTVKHIKQSEENFNPNCSFWSYSKRTMTGYW   900
 901  STQGCRLLTTNKTHTTCSCNHLTNFAVLMAHVEVKHSDAVHDLLLDVITW   950
 951  VGILLSLVCLLICIFTFCFFRGLQSDRNTIHKNLCISLFVAELLFLIGIN  1000
1001  RTDQPIACAVFAALLHFFFLAAFTWMFLEGVQLYIMLVEVFESEHSRRKY  1050
1051  FYLVGYGMPALIVAVSAAVDYRSYGTDKVCWLRLDTYFIWSFIGPATLII  1100
1101  MLNVIFLGIALYKMFHHTAILKPESGCLDNINYEDNRPFIKSWVIGAIAL  1150
1151  LCLLGLTWAFGLMYINESTVIMAYLFTIFNSLQGMFIFIFHCVLQKKVRK  1200
1201  EYGKCLRTHCCSGRSTESSIGSGKTSGSRTPGRYSTGSQSRIRRMWNDTV  1250
1251  RKQSESSFITGDINSSASLNRGAMANHLISNALLRPHGTNNPYNTLLGEP  1300
1301  AVCNNPSVSMYNAQEGLLNNARDTSVMDTLPLNGNHGNSYSIASGEYLSN  1350
1351  CVQIIDRGYNHNETALEKKILKELTSNYIPSYLNNHERSSEQNRNLMNKL  1400
1401  VNNLGSGSEDDAIVLDDATSFNHEESLGLELIHEESDAPLLPPRVYSTEN  1450
1451  HQLHHYTRRRIPQDHSESFFPLLTNEHTEDLQSPHRDSLYTSMPALAGVP  1500
1501  TAESVTTSTQTEPPPAKCGDAEDVYYKSMPNLGSRNHVHQLHTYYQLGRG  1550
1551  SSDGFIVPPNKDGTPPEGSSKGPAHLVTSL                      1580

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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