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

NucPred

Fetching P10686 from www.uniprot.org...

The NucPred score for your sequence is 0.90 (see score help below)

   1  MAGVGTPCANGCGPSAPSEAEVLHLCRSLEVGTVMTLFYSKKSQRPERKT    50
  51  FQVKLETRQITWSRGADKIEGSIDIREIKEIRPGKTSRDFDRYQEDPAFR   100
 101  PDQSHCFVILYGMEFRLKTLSLQATSEDEVNMWIKGLTWLMEDTLQAATP   150
 151  LQIERWLRKQFYSVDRNREDRISAKDLKNMLSQVNYRVPNMRFLRERLTD   200
 201  FEQRSGDITYGQFAQLYRSLMYSAQKTMDLPFLETNTLRTGERPELCQVS   250
 251  LSEFQQFLLEYQGELWAVDRLQVQEFMLSFLRDPLREIEEPYFFLDELVT   300
 301  FLFSKENSVWNSQLDAVCPETMNNPLSHYWISSSHNTYLTGDQFSSESSL   350
 351  EAYARCLRMGCRCIELDCWDGPDGMPVIYHGHTLTTKIKFSDVLHTIKEH   400
 401  AFVASEYPVILSIEDHCSIAQQRNMAQHFRKVLGDTLLTKPVDIAADGLP   450
 451  SPNQLKRKILIKHKKLAEGSAYEEVPTSVMYSENDISNSIKNGILYLEDP   500
 501  VNHEWYPHYFVLTSSKIYYSEETSSDQGNEDEEEPKEASGSTELHSSEKW   550
 551  FHGKLGAGRDGRHIAERLLTEYCIETGAPDGSFLVRESETFVGDYTLSFW   600
 601  RNGKVQHCRIHSRQDAGTPKFFLTDNLVFDSLYDLITHYQQVPLRCNEFE   650
 651  MRLSEPVPQTNAHESKEWYHASLTRAQAEHMLMRVPRDGAFLVRKRNEPN   700
 701  SYAISFRAEGKIKHCRVQQEGQTVMLGNSEFDSLVDLISYYEKHPLYRKM   750
 751  KLRYPINEEALEKIGTAEPDYGALYEGRNPGFYVEANPMPTFKCAVKALF   800
 801  DYKAQREDELTFTKSAIIQNVEKQDGGWWRGDYGGKKQLWFPSNYVEEMI   850
 851  NPAILEPEREHLDENSPLGDLLRGVLDVPACQIAIRPEGKNNRLFVFSIS   900
 901  MPSVAQWSLDVAADSQEELQDWVKKIREVAQTADARLTEGKMMERRKKIA   950
 951  LELSELVVYCRPVPFDEEKIGTERACYRDMSSFPETKAEKYVNKAKGKKF  1000
1001  LQYNRLQLSRIYPKGQRLDSSNYDPLPMWICGSQLVALNFQTPDKPMQMN  1050
1051  QALFMAGGHCGYVLQPSTMRDEAFDPFDKSSLRGLEPCVICIEVLGARHL  1100
1101  PKNGRGIVCPFVEIEVAGAEYDSTKQKTEFVVDNGLNPVWPAKPFHFQIS  1150
1151  NPEFAFLRFVVYEEDMFSDQNFLAQATFPVKGLKTGYRAVPLKNNYSEDL  1200
1201  ELASLLIKIDIFPAKENGDLSPFSGTSLRERASDASSQLFHVRAREGSFE  1250
1251  ARYQQPFEDFRISQEHLADHFDSRERRAPRRTRVNGDNRL            1290

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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