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

NucPred

Fetching Q09140 from www.uniprot.org...

The NucPred score for your sequence is 0.75 (see score help below)

   1  MRWGFWFAIATLITICYAAKPLDVKIAATFNAPSFSALIAESLYQEKKEG    50
  51  FIWYLNHLSDLLDAENTTEKELYINVVNSLKREYVLSDEELSSLQFSLGL   100
 101  FSGAPKLQAFSSIVQSRSCDCDTWLQLDEESQVCFSDLPKDSPLFSKLYS   150
 151  KNPLDYEVVKTSATGIPYAVVVTSFERDLIPFHELYYKLALEGKCNYVIR   200
 201  YSPPSSSKLNSKLYVKGFGTHVSLKRTDYLVVDDREFPREKGDNPASFTS   250
 251  SRNKRSNERLFGMTSDSLQTVTPDKIAILDLLATQSIASSTDMLTAFREL   300
 301  TQDFPIYAHYLSIQPDVSNDLIEELNQFQSQYVPEGINTIWLNGLSLDLE   350
 351  ETDAFSILSLIKKEKDMFDRFEALGIKSSKVLDIVTNEAFANEDSDFKFV   400
 401  KFHCQDDIEDWKAIHWVNEIESNPKYDNWPKSIQILLKPIYPGQLHMLGK   450
 451  QLHTVIYPIFPSSPSSLPLLSELIQFSRRPSPVQTGMVCAANDDDEFAQT   500
 501  VCKSFFYISKESGTDSALKFLYKCLNSDSSADLYSLLEEHLPLSEHDDDT   550
 551  LANLKKDLSSSFFDHYMSKSNSWVNRLGIDSSASEVIVNGRIISHDENYD   600
 601  RSMYGIFLEDIPEVQIAVAEGKISEDDNLLDFILRDASLTRNPLVYPSAK   650
 651  SSIKSIDIKRVLENVGSLNHEDILLIGSSNAKYSFWLVADFNEKEGLEIL   700
 701  SLLADLLSENKDANLMLIQEGKNHVVPPLFAKLLSSPKRSSKHLQEILNS   750
 751  SLDPSSGVVNDMDKALKFLKKSKAVVKELGLTGECKSALLLNGRMICSFS   800
 801  VDSLNTADLKMLMQMEYDNYLSKLSNIAGSSRRLKNSRAISFLSSYLKTL   850
 851  ESTPMSTSSPTKEEKLFPRDFIYNKLGVGNATFETDDFSKAYYQFVAVLD   900
 901  PLSKDSQKWSAILEAVSKLNGVGVRIHFNPKQTLSELPLTRFYRYSISAE   950
 951  PEFDALGHLEESYVEFDNLPADTLLTMDIEARDAWTVMQKDVDIDLFNIK  1000
1001  LEHTSEAEALDSHTAIYELKNILVQGYSQEEFRKSPPRGMQLKLGNLTNS  1050
1051  HVTDTIVLSNLGYFQLKANPGVWTLEPMDGRSSQFYEILSLNKKNSYKDP  1100
1101  QVIVDSFEGVTLNPVMRRKPGFESADIMDEDLSSHKFFDKIKKSLSFFNF  1150
1151  KRKEASINIFSVASGHLYERFLYIMTKSVIEHTDKKVKFWFIENFLSPSF  1200
1201  KSSIPAIAKKYNFEYEYITYNWPHWLRKQEEKQREIWGYKILFLDVLFPL  1250
1251  ELHKVIYVDADQIVRADLQELMDMDLHGAPYGYTPMCDSREEMEGFRFWK  1300
1301  KGYWKKFLRGLKYHISALYVVDLDRFRKMGAGDLLRRQYQLLSADPNSLS  1350
1351  NLDQDLPNHLQHLIPIYSLPQDWLWCETWCSDESLKTAKTIDLCQNPLTK  1400
1401  EKKLDRARRQVSEWTSYDNEIASVLQTASSQSDKEFEEKDNNSSPDEL    1448

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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