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

NucPred

Fetching P24349 from www.uniprot.org...

The NucPred score for your sequence is 0.73 (see score help below)

   1  MSDEEDIDESFEIEEDGISITDARGNSLKAQQIAGKERNLDPEADDLEVV    50
  51  VNFYEAGDGTFQLQLPKLTAVKPVDKVNDVLDFINFDKKVCDGIHSSIKL   100
 101  VSQRDQTGPAPFPKHKLTCAHCDWSFDNVMKLVRHRGVHKNVGVYMCQVC   150
 151  LTLFGHTYNLFMHWRTSCSQTSTTATDIEIQKAETPYLHRNVLNVLGSLN   200
 201  RASQYYCTGGYVFLPSDWCITNKEIVMEKDHMSSCHLCHLPVPNKFLEAH   250
 251  GNVHRGRFRIDGRIYGDYFCHICGTVFIEQDNLFKHWRLHCEEVIAYTPV   300
 301  DQYLSNTELATLAWLVLQTTISQADIECLRVSSSLITEKLAKEHAERHGI   350
 351  ANSMHKYYHFPQEIWPLKTFVNLDLVNDAIPISGENSFKIKDPKRPVHIM   400
 401  NLLATACPGFYATGKTFNMICSTKKSESDTKKVYRVILRYTTEGSVIQSY   450
 451  DFTARSFPKLRVDSETPEGVFSHPLADFNVESNEAIVCHKCDSKKLTITF   500
 501  STEVRLKYHLLRHSESRKDGYHCAICKIIVYNRSHEEHWINDCIPLQKLY   550
 551  RDQKDRECFDAEFAAKCASIIKKLRIRTLIRWKERANEDWVETKQTPDRI   600
 601  GEDFAIKFQVGTTALKTLMAGLEEHYKNAQARHEAYKYSEENFLPPLSTP   650
 651  VVVCFHCGTRCHYTLLHDHLDYCHYWPRNKRLVNEEFHKWKKNGCRNTWR   700
 701  VMKSVAEAMQIEVPFISEEQYSKILDYHTYFCNDTRYKVQDSINNWNDCS   750
 751  TIRDVDLSEKLSVAEIVQKGEDSVMAPEPDIIKNVYFPSARIITDNMLLR   800
 801  MTEINLNDVVQRDPITKEELTGKFKEVQDEQDAILFGDYRAVLRSKGIMV   850
 851  NSISDFVAPPDELAKAKASQESAGQESVDHRNRREREFIQQYMGKDLALE   900
 901  AAARENGRLVEVDEEAEDYELTPKELNARRLVERNRHREMCKTRCEHGEY   950
 951  DYEKFKARQVPINPAKMKERKYLTRVVHESGPDDDVCPDEPENNIIAFSP  1000
1001  KYENSLSDFRISAIGFREKYLADDKKKRNGIPIRKMTEAQKGVALDYDTL  1050
1051  MARHGGRPDVIMNPAGTVFVGGFVFDRKPTCQDNMQTVYVLRNGYAHRYR  1100
1101  IYHCEDTNGIYKFVWPQEQSFDPDSLAKSARVRMVKQVKSPEHMIHHIEE  1150
1151  IDESIGHNYRLNRKRRNSETREHELIELDTDDLNEPSTSDGRYSFGHHGY  1200
1201  R                                                   1201

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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