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

NucPred

Fetching Q86UU1 from www.uniprot.org...

The NucPred score for your sequence is 0.96 (see score help below)

   1  MDALNRNQIGPGCQTQTMVQKGPLDLIETGKGLKVQTDKPHLVSLGSGRL    50
  51  STAITLLPLEEGRTVIGSAARDISLQGPGLAPEHCYIENLRGTLTLYPCG   100
 101  NACTIDGLPVRQPTRLTQGCMLCLGQSTFLRFNHPAEAKWMKSMIPAGGR   150
 151  APGPPYSPVPAESESLVNGNHTPQTATRGPSACASHSSLVSSIEKDLQEI   200
 201  MDSLVLEEPGAAGKKPAATSPLSPMANGGRYLLSPPTSPGAMSVGSSYEN   250
 251  TSPAFSPLSSPASSGSCASHSPSGQEPGPSVPPLVPARSSSYHLALQPPQ   300
 301  SRPSGARSESPRLSRKGGHERPPSPGLRGLLTDSPAATVLAEARRATESP   350
 351  RLGGQLPVVAISLSEYPASGALSQPTSIPGSPKFQPPVPAPRNKIGTLQD   400
 401  RPPSPFREPPGSERVLTTSPSRQLVGRTFSDGLATRTLQPPESPRLGRRG   450
 451  LDSMRELPPLSPSLSRRALSPLPTRTTPDPKLNREVAESPRPRRWAAHGA   500
 501  SPEDFSLTLGARGRRTRSPSPTLGESLAPHKGSFSGRLSPAYSLGSLTGA   550
 551  SPCQSPCVQRKLSSGDLRVPVTRERKNSITEISDNEDDLLEYHRRQRQER   600
 601  LREQEMERLERQRLETILNLCAEYSRADGGPEAGELPSIGEATAALALAG   650
 651  RRPSRGLAGASGRSSEEPGVATQRLWESMERSDEENLKEECSSTESTQQE   700
 701  HEDAPSTKLQGEVLALEEERAQVLGHVEQLKVRVKELEQQLQESAREAEM   750
 751  ERALLQGEREAERALLQKEQKAVDQLQEKLVALETGIQKERDKEAEALET   800
 801  ETKLFEDLEFQQLERESRVEEERELAGQGLLRSKAELLRSIAKRKERLAI   850
 851  LDSQAGQIRAQAVQESERLARDKNASLQLLQKEKEKLTVLERRYHSLTGG   900
 901  RPFPKTTSTLKEMEKLLLPAVDLEQWYQELMAGLGTGPAAASPHSSPPPL   950
 951  PAKASRQLQVYRSKMDGEATSPLPRTRSGPLPSSSGSSSSSSQLSVATLG  1000
1001  RSPSPKSALLTQNGTGSLPRNLAATLQDIETKRQLALQQKGQQVIEEQRR  1050
1051  RLAELKQKAAAEAQCQWDALHGAAPFPAGPSGFPPLMHHSILHHLPAGRE  1100
1101  RGEEGEHAYDTLSLESSDSMETSISTGGNSACSPDNMSSASGLDMGKIEE  1150
1151  MEKMLKEAHAEKNRLMESREREMELRRQALEEERRRREQVERRLQSESAR  1200
1201  RQQLVEKEVKMREKQFSQARPLTRYLPIRKEDFDLKTHIESSGHGVDTCL  1250
1251  HVVLSSKVCRGYLVKMGGKIKSWKKRWFVFDRLKRTLSYYVDKHETKLKG  1300
1301  VIYFQAIEEVYYDHLRSAAKKRFFRFTMVTESPNPALTFCVKTHDRLYYM  1350
1351  VAPSAEAMRIWMDVIVTGAEGYTQFMN                         1377

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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