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

NucPred

Fetching P49021 from www.uniprot.org...

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

   1  MDWLLATPQLYSAFSSLGCLEGDTYVVNPNALAILEEINYKLTYEDQTLR    50
  51  TFRRAIGFGQNVRSDLIPLLENAKDDAVLESVIRILVNLTVPVECLFSVD   100
 101  VMYRTDVGRHTIFELNKLLYTSKEAFTEARSTKSVVEYMKHILESDPKLS   150
 151  PHKCDQINNCLLLLRNILHIPETHAHCVMPMMQSMPHGISMQNTILWNLF   200
 201  IQSIDKLLLYLMTCPQRAFWGVTMVQLIALIYKDQHVSTLQKLLSLWFEA   250
 251  SLSESSEDNESNTSPPKQGSGDSSPMLTSDPTSDSSDNGSNGRGMGGGMR   300
 301  EGTAATLQEVSRKGQEYQNAMARVPADKPDGSEEASDMTGNDSEQPGSPE   350
 351  QSQPAGESMDDGDYEDQRHRQLNEHGEEDEDEDEVEEEEYLQLGPASEPL   400
 401  NLTQQPADKVNNTTNPTSSAPQGCLGNEPFKPPPPLPVRASTSAHAQMQK   450
 451  FNESSYASHVSAVKLGQKSPHAGQLQLTKGKCCPQKRECPSSQSELSDCG   500
 501  YGTQVENQESISTSSNDDDGPQGKPQHQKPPCNTKPRNKPRTIMSPMDKK   550
 551  ELRRKKLVKRSKSSLINMKGLVQHTPTDDDISNLLKEFTVDFLLKGYSYL   600
 601  VEELHMQLLSNAKVPIDTSHFFWLVTYFLKFAAQLELDMEHIDTILTYDV   650
 651  LSYLTYEGVSLCEQLELNARQEGSDLKPYLRRMHLVVTAIREFLQAIDTY   700
 701  NKVTHLNEDDKAHLRQLQLQISEMSDLRCLFVLLLRRFNPSIHSKQYLQD   750
 751  LVVTNHILLLILDSSAKLGGCQTIRLSEHITQFATLEVMHYYGILLEDFN   800
 801  NNGEFVNDCIFTMMHHIGGDLGQIGVLFQPIILKTYSRIWEADYELCDDW   850
 851  SDLIEYVIHKFMNTPPKSPLTIPTTSLTEMTKEHNQEHTVCSWSQEEMDT   900
 901  LYWYYVQSKKNNDIVGKIVKLFSNNGNKLKTRISIIQQLLQQDIITLLEY   950
 951  DDLMKFEDAEYQRTLLTTPTSATTESGIEIKECAYGKPSDDVQILLDLII  1000
1001  KENKAQHLLWLQRILIECCFVKLTLRSGLKVPEGDHIMEPVAYHCICKQK  1050
1051  SIPVVQWNNEQSTTMLYQPFVLLLHKLGIQLPADAGSIFARIPDYWTPET  1100
1101  MYGLAKKLGPLDKLNLKFDASELEDATASSPSRYHHTGPRNSLSSVSSLD  1150
1151  VDLGDTEELALIPEVDAAVEKAHAMASTPSPSEIFAVPKTKHCNSIIRYT  1200
1201  PDPTPPVPNWLQLVMRSKCNHRTGPSGDPSDCIGSSSTTVDDEGFGKSIS  1250
1251  AATSQAASTSMSTVNPTTTLSLNMLNTFMGSHNENSSSSGCGGTVSSLSM  1300
1301  VALMSTGAAGGGGNTSGLEMDVDASMKSSFERLEVNGSHFSRANNLDQEY  1350
1351  SAMVASVYEKEKELNSDNVSLASDLTRMYVSDEDDRLERTEIRVPHYH    1398

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.)

Go back to the NucPred Home Page.