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

NucPred

Fetching Q09417 from www.uniprot.org...

The NucPred score for your sequence is 0.72 (see score help below)

   1  MFIPNDRPSVLQLPKHEKDSTAADIKSIVANRDRRLIAVATNDAIYIWLA    50
  51  NPQLLLCSVGVIDANFKETRGELKEIYWKPDSTSIAVTTNQCKILIYNLD   100
 101  LRDDEQCYNFTDSADPYFQRNSPELFIKGSRPTAHLHPTIIINLADIPTC   150
 151  CVPSRDEFLVCLQNGFTHHVTWTGEIIASLSFRASSIPFSVDQLQSKSEN   200
 201  ITSKSTYIFDAVYAPLLGGFAIVLSDGQGALLTSNDPNFAPNAILGVWAP   250
 251  NMKDATCCDVNHKFLLILFGCKNGDVCAYNIDELNGSLVQSFRVAPKVTN   300
 301  GPDLTNRLGPVHRITALANGYGFGAIWSPLSGAHALPRLVAVFTSFGAQS   350
 351  FCNLEGVVEEDQNDRYTAIEWGPEGFQLWLGTENELMMQPFVRSASCSSP   400
 401  AMEHCDRAVLMSDSQVLISAARDREAEACAPHSVWDHITVTHEYLSSNWP   450
 451  LRYASTDRNYKHLVVAGDQGMAYCSLSNRRWKIFGNETQEKNLLVTGGVF   500
 501  IWNDDVIGVVGVAADTDKSHLSFYPISQRLDSRYASVVDLEHKSVMSVLR   550
 551  DDVCAVFDISAQITLYKLTAHLETGRDAFTKVSTEIVTVIRINEIVPHPT   600
 601  CIVSLQMTQLNLDVRGKLSPAFYSSIDTVLVNISGRLITLSVNEDGKLHQ   650
 651  PMVIASYVEKMWHDRCQVSQSTQSQNQDLPWKNHRRNGSNVSIQSVSTST   700
 701  TSEPSSPMNQSCSSHLSNALWIACGAKGIKVWMPLVPGKRNLATQEMTFI   750
 751  AKRIMLPFELDIYPIVISAKDCLAMGVESQLQHVARASRNQGQMESITMY   800
 801  GLHRNSEVFVHHLLRQLLKRNLGVFALELAGACRSLPHFTHALELLLHGV   850
 851  LEEEATSSEPIPDPLLPRCVAFIHEFPEFLKTVAHCARKTELALWRTLFD   900
 901  VTGSPNALFEECLQLKQLENAASFVIVLQNLETTEVSMDQAARLVKEALE   950
 951  EKKWTIAKEMVRFARSIGSEDIDAFFRTPPPSAKTSLSRRPTVSSPSADS  1000
1001  STEFVINRFQAGAAGGRLNKVRHSQSTEQKDAPRKDSIGGSSKDKMALSW  1050
1051  GLSGELSPQLATNRLAAKMTSILEDHAWHLLNNYWLLDLGFFWSELQFDL  1100
1101  LGLLETRRKQISLSPKTTNENCFLIEDFALALTRLHAQFSWPYPLIGSQF  1150
1151  VHQIEKKLGNIRVSQSTASLNGLLNDSLDNIKKPKARKLERTVVDLNGAR  1200
1201  SRIRETDIEASEEDVEIQEAVLERVRGSAVELAPVIDRSPSTSSSMNHHA  1250
1251  PLAPPSPSSCDSRSLAGDCYQNTDFLVGEKSSRGNLQSSHQLELLLSLFS  1300
1301  QTATIDWIFLFCLLSRDERKLRQEINVSMVRRAGEKSFARVRFACSELSR  1350
1351  WAVEKCCGYVALLQAFDAHLAVVAEQAGCADLKFSPDNENRKASQKTSAD  1400
1401  DPKRGRRRADSGSSKLNNSFSNPKLNGMNGGRRERSRSADRAHKSVKRYD  1450
1451  DVVCAEDALEKANEEGCSIM                                1470

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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