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

NucPred

Fetching Q6ZBH9 from www.uniprot.org...

The NucPred score for your sequence is 0.62 (see score help below)

   1  MAHVSFKSKEADSMSRWSKYLSTEESPPSASLSWRAMGVDGPQGSASGQK    50
  51  HLQMEPVVQLSKVAEGLLAKMYRLNSILDYPDPNAHTFSEAFWKAGVMPN   100
 101  FPKICITLSKKFPEHPNKLQLEKVDKFALDALNENAEGYMQNLEQWITLL   150
 151  LDLLEFREQALRLILDLSSTVITLLPHQNSLILHAFMDLFCSFVRVNLFS   200
 201  DKIPRKMILQVYNILHIMLKGGRDCEFYHRLVQFVDLYDPPVKGLHEDLN   250
 251  FVSPRIGEVLEAVGPIIFLSTDTKKLRNEGFLSPFHPRYPDILTNSAHPM   300
 301  RAQDLANVTSYREWVLLGYLVCPDELLRVTSIDVAMVVLKENLVLSLFRD   350
 351  EYILLHENYQLYVLPKVLESKRMAKSGRTKQKEADLEYNVAKQVEKMLME   400
 401  VHEQALVSADALHHERRILLKQEIGRMVLFFTDQPSLLAPNIQMVFSALA   450
 451  LAQCEVVWYFQHVGIASSKSSRGRTVDIDAADPTIGFLLDGMGKLCCLVR   500
 501  KYIAAIKGYALSYLSSCAGRIRFLLGTPGMVALDLDATLKGLFQQVLHCL   550
 551  ENIPKPQGENVPAITCDLTDLRKHWLSILMIVTSSRSSVNIRHLEKATVS   600
 601  TGKEGLVSEGNAAYNWSRCVDELEGQLSKHGSLKKLYFYHQHLTTVFRNT   650
 651  MFGPEGRPQHCCAWLGAACCFPECASSIIPEEVNKIGRDSISYVESLIES   700
 701  IMGGLEGLINILDSEGGFGSLEMQLSPEQAAIRLNNATRAKAVSGLLAPG   750
 751  HESYPDNSSSVKMLEAAMQRLTSLCSVLNDMEPICVLNHVFILREYMRDC   800
 801  IIGNFRRRFHSMIRTDSCLQRPSVIESLLRRHLSIIHLAEQHISMDLTEG   850
 851  IREVLLAESFTGPFPNLQVFETPTETHGGGSAIDIISNWYIDNFVKDASR   900
 901  TGVVFDASQNCFRSSQPIGGGYLAEAFTDKRELKALVRLFGGYGVDRLDK   950
 951  LLREHTSALLNCIDSALRSNRDALEGLAGSVNSGDRIERDANLKQIIDIE  1000
1001  TLADFCIQAGQAITFRRLLVEAVGAVLEEKVPLIYSLLKGLAMQLPEEVP  1050
1051  DKNEIIRLRRVASSVGVGDKHDAEWVHSILAEIGSANDNSWTLLPYLCAA  1100
1101  FMASNMWSTTAYDVNTGGFSNNLHCLARCVSAVVGGSEYTRMEREHRRSS  1150
1151  LSNGHMDELQEPELLSRVSAEANIKSAMQLYVKLSAGLVLDSWNDTSRPY  1200
1201  IVPKLIFLDQLCEMSPYLPRSTLEVHIPYTILRSIYHQLYGASLMATEPM  1250
1251  EPSPRQSPLISLAHASPSMKQNRADTTPRSHTFEPGYHSSSGSQYDEGYE  1300
1301  GDRRTGERQLRSMRRSGPLDYTGTRKVKFVEGSSSGSHGAGSGSLQRFAV  1350
1351  SRSGPLSYK                                           1359

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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