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

NucPred

Fetching Q09891 from www.uniprot.org...

The NucPred score for your sequence is 0.49 (see score help below)

   1  MESVEEKSKQRRWLPNFKALRLKVYRLADRLNIPLADAARVELEEYDGSD    50
  51  PQSLRGLQKLPRTLYFGLPLPDSELDDTGEAKRWFPRNKIRTAKYTPIDF   100
 101  IPKNIFLQFQNVANLFFLFLVILQSISIFGEQVNPGLAAVPLIVVVGITA   150
 151  VKDAIEDFRRTMLDIHLNNTPTLRLSHYQNPNIRTEYISYFRRFKKRISA   200
 201  LFRVFLAKQEEKKRAKRLNDAVPLEDMAGSESRPSYDSIFRESFEAKRSF   250
 251  EDSKGKVPLSALDGTATILQSRPMDIIDYEAEATGECHFKKTYWKDVRVG   300
 301  DFVKVMDNDEIPADIVIINSSDPEGICYIETKNLDGETNLKMRHALTCGK   350
 351  NVVDEASCERCRFWIESEPPHANLYEYNGACKSFVHSEAGGSDTSQTVSE   400
 401  PISLDSMLLRGCVLRNTKWVIGVVVFTGDDTKIMLNSGAPPLKRSRITRN   450
 451  LNWNVYLNFIILFSMCFVCAVVEGIAWRGHSRSSYYFEFGSIGGSPAKDG   500
 501  VVTFFTGVILFQNLVPISLYISIEIVKTIQAIFIYFDKDMYYKKLKYACT   550
 551  PKSWNISDDLGQVEYIFSDKTGTLTQNVMEFKKCTINGVAYGEAFTEAMA   600
 601  GMAKREGKDTEELTLQKQSFIERDRMQMISQMRNMHDNKYLVDDNLTFIS   650
 651  SQFVHDLAGKAGEEQSLACYEFFLALALCHSVVADRVGDRIVYKAQSPDE   700
 701  AALVGTARDVGFVFLDQRRDIMVTRALGETQRFKLMDTIEFSSARKRMSV   750
 751  IVKGPDNRYVLICKGADSIIFERLEPNEQVELRKTTSEHLRIFALEGLRT   800
 801  LCIAKRELTEEEYYEWKEKYDIAASAIENREEQIEEVADLIESHLTLLGG   850
 851  TAIEDRLQEGVPDSIALLAQAGIKLWVLTGDKMETAINIGFSCNLLDAGM   900
 901  DMIKFDVDQEVSTPELEVILADYLYRYFGLSGSVEELEAAKKDHDTPSGS   950
 951  HALVIDGSVLKRVLDGPMRTKFLLLCKRCKAVLCCRVSPAQKADVVQLVR  1000
1001  ESLEVMTLAIGDGANDVAMIQKADIGVGIVGEEGRAAAMSADYAIGQFRF  1050
1051  LSKLVLVHGRWDYNRVAEMVNNFFYKSVVWTFTLFWYQIYNNFDANYLFD  1100
1101  YTYVMLFNLIFSSLPVIVMGVYDQDVNADLSLRIPQLYKRGILQLNSARK  1150
1151  IFIGYMLDGFYQSVICFFFSFLVINNVTTAAQNGRDTMAVQDLGVYVAAP  1200
1201  TIMVVDTYVILNQSNWDVFSIGLWALSCLTFWFWTGVYSQSLYTYEFYKS  1250
1251  ASRIFRTPNFWAVLCGTIVSCLFPKFLFMTTQKLFWPYDVDIIRESYRTK  1300
1301  RLHELDEEEEIENAEQSPDWASSTLQVPFNASSSSLATPKKEPLRLDTNS  1350
1351  LTLTSSMPRSFTPSYTPSFLEGSPVFSDEILNRGEYMPHRGSISSSEQPL  1400
1401  RP                                                  1402

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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