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

NucPred

Fetching Q7G193 from www.uniprot.org...

The NucPred score for your sequence is 0.34 (see score help below)

   1  MGEKAIDEDKVEAMKSSKTSLVFAINGQRFELELSSIDPSTTLVDFLRNK    50
  51  TPFKSVKLGCGEGGCGACVVLLSKYDPLLEKVDEFTISSCLTLLCSIDGC   100
 101  SITTSDGLGNSRVGFHAVHERIAGFHATQCGFCTPGMSVSMFSALLNADK   150
 151  SHPPPRSGFSNLTAVEAEKAVSGNLCRCTGYRPLVDACKSFAADVDIEDL   200
 201  GFNAFCKKGENRDEVLRRLPCYDHTSSHVCTFPEFLKKEIKNDMSLHSRK   250
 251  YRWSSPVSVSELQGLLEVENGLSVKLVAGNTSTGYYKEEKERKYERFIDI   300
 301  RKIPEFTMVRSDEKGVELGACVTISKAIEVLREEKNVSVLAKIATHMEKI   350
 351  ANRFVRNTGTIGGNIMMAQRKQFPSDLATILVAAQATVKIMTSSSSQEQF   400
 401  TLEEFLQQPPLDAKSLLLSLEIPSWHSAKKNGSSEDSILLFETYRAAPRP   450
 451  LGNALAFLNAAFSAEVTEALDGIVVNDCQLVFGAYGTKHAHRAKKVEEFL   500
 501  TGKVISDEVLMEAISLLKDEIVPDKGTSNPGYRSSLAVTFLFEFFGSLTK   550
 551  KNAKTTNGWLNGGCKEIGFDQNVESLKPEAMLSSAQQIVENQEHSPVGKG   600
 601  ITKAGACLQASGEAVYVDDIPAPENCLYGAFIYSTMPLARIKGIRFKQNR   650
 651  VPEGVLGIITYKDIPKGGQNIGTNGFFTSDLLFAEEVTHCAGQIIAFLVA   700
 701  DSQKHADIAANLVVIDYDTKDLKPPILSLEEAVENFSLFEVPPPLRGYPV   750
 751  GDITKGMDEAEHKILGSKISFGSQYFFYMETQTALAVPDEDNCMVVYSST   800
 801  QTPEFVHQTIAGCLGVPENNVRVITRRVGGGFGGKAVKSMPVAAACALAA   850
 851  SKMQRPVRTYVNRKTDMITTGGRHPMKVTYSVGFKSNGKITALDVEVLLD   900
 901  AGLTEDISPLMPKGIQGALMKYDWGALSFNVKVCKTNTVSRTALRAPGDV   950
 951  QGSYIGEAIIEKVASYLSVDVDEIRKVNLHTYESLRLFHSAKAGEFSEYT  1000
1001  LPLLWDRIDEFSGFNKRRKVVEEFNASNKWRKRGISRVPAVYAVNMRSTP  1050
1051  GRVSVLGDGSIVVEVQGIEIGQGLWTKVKQMAAYSLGLIQCGTTSDELLK  1100
1101  KIRVIQSDTLSMVQGSMTAGSTTSEASSEAVRICCDGLVERLLPVKTALV  1150
1151  EQTGGPVTWDSLISQAYQQSINMSVSSKYMPDSTGEYLNYGIAASEVEVN  1200
1201  VLTGETTILRTDIIYDCGKSLNPAVDLGQIEGAFVQGLGFFMLEEFLMNS  1250
1251  DGLVVTDSTWTYKIPTVDTIPRQFNVEILNSGQHKNRVLSSKASGEPPLL  1300
1301  LAASVHCAVRAAVKEARKQILSWNSNKQGTDMYFELPVPATMPIVKEFCG  1350
1351  LDVVEKYLEWKIQQRKNV                                  1368

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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