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

NucPred

Fetching Q9SKX0 from www.uniprot.org...

The NucPred score for your sequence is 0.47 (see score help below)

   1  MAITLTNFTFLYMDANLKRLGDIVLGFGANVVTLLLILILTITRRNGRCN    50
  51  RRKSYIEKCLLYVTPALGACLSCVDLVLLVRTNRRREVILCFVPLSGFVM   100
 101  WIAVILSLKFACCACHVFTSQILCFWWIFRFLTDALHLNMIFTLQRVQEI   150
 151  CLIMLDIAFGISINVLRIKQAHPKIIPLEDPLIEDDDDQKRIVRRLFLEK   200
 201  NGSWWDLFTFGYIGSIMKHGSVKQLELENLLTLPPEMDPFTCCENLLRCW   250
 251  QLQECNNYSTPSLIWSIYGVYGWPYFRLGLLKVFNDCIGFAGPLLLNRLI   300
 301  KSFLDTQYTFRLSKLKLKLRSSIMSVIYRKCLWVNTANRSGFSEGEIQTF   350
 351  MSVDADRIVNLCNSLHDLWSLPLQIGIALYLLYTQVKFAFLSGLAITILL   400
 401  IPVNKWISVLIASATEKMMKLKDERIRKTGELLTNIRTLKMYGWDNWFAD   450
 451  WLKETRATEVTHLATRKYLDAWCVFFWATTPTLFSLCTFGLFALMGHQLD   500
 501  AATVFTCLALFNSLISPLNSFPWVINGLIDAFISTRRVSKFLCCLEHSRD   550
 551  FSIDSGFTSEDLAVCVEDASCTWSSNVEEDYNLTIKQVSLRVPKGSFVAV   600
 601  IGEVGSGKTSLLNSLLGEMRCVHGSILLNGSVAYVPQVPWLLSGTVRENI   650
 651  LFGKPFDSKRYFETLSACALDVDISLMVGGDMACIGDKGLNLSGGQRARF   700
 701  ALARAVYHGSDMYLLDDVLSAVDSQVGCWILQRALLGPLLNKKTRVMCTH   750
 751  NIQAISCADMIVVMDKGKVNWSGSVTDMPKSISPTFSLTNEFDMSSPNHL   800
 801  TKRKETLSIKEDGVDEISEAAADIVKLEERKEGRVEMMVYRNYAVFSGWF   850
 851  ITIVILVSAVLMQGSRNGNDLWLSYWVDKTGKGVSHYSTSFYLMVLCIFC   900
 901  IINSILTLVRAFSFAFGGLKAAVHVHNALISKLINAPTQFFDQTPSGRIL   950
 951  NRFSSDLYTIDDSLPFILNILLANFVGLLGIIVVLSYVQVLFLLLLLPFW  1000
1001  YIYSKLQVFYRSTSRELRRLDSVSRSPIYASFTETLDGSSTIRAFKSEEH  1050
1051  FVGRFIEHLTLYQRTSYSEIIASLWLSLRLQLLGSMIVLFVAVMAVLGSG  1100
1101  GNFPISFGTPGLVGLALSYAAPLVSLLGSLLTSFTETEKEMVSVERVLQY  1150
1151  MDVPQEEVSGPQSLSDKWPVHGLVEFHNVTMRYISTLPPALTQISFTIQG  1200
1201  GMHVGVIGRTGAGKSSILNALFRLTPVCSGEILVDGKNISHLPIRELRSC  1250
1251  LAVVPQSPFLFQGSLRDNLDPLGLSEDWRIWEILDKCKVKAAVESVGGLD  1300
1301  SYVKESGCSFSVGQRQLLCLARALLKSSKILCLDECTANIDVHTASLLHN  1350
1351  TISSECKGVTVITIAHRISTVVDLDSILILDRGILVEQGKPQHLLQDDSS  1400
1401  TFSSFVRASQ                                          1410

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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