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

NucPred

Fetching Q09706 from www.uniprot.org...

The NucPred score for your sequence is 0.82 (see score help below)

   1  MTIHQGGNSVIDNVPYSLNTNVNDSIYSEKGTGRKDAEDHTPSKITDLEK    50
  51  NVDHSIPSFPENDPKNYSEFVNLNPPKRPDLEHTRGSSWHTASENVNDLA   100
 101  ANDSTRVQTPEFITQTMEDENVEVPPLERDERDAAAAHTSKANRNSARQM   150
 151  WAQLMASVRKFKREDEKPILKENLPAINLFEAGIPASLPIAKHFIRDKSG   200
 201  QPVLPIITDLIKVSVLDVEPKHNRIHSTFTIQVEYGTGPHAIRWLIYRQL   250
 251  RDFINLHSHFLFFEFQHRFSGRRMKLPKFPKEVLPYLVKLRGYQKILYSN   300
 301  PSDQLIDETHSISDISWESHSQDGDRTTGQPRHANNGRKKHGNFWTIQGN   350
 351  TLGVYLQEMIHNLQFFPEVNVLYSFLEFSSLGLYLAGAGTFHGKEGFATL   400
 401  KRNYSPTQYMLCCNTTMMKTRSQPFWIIVSESCIILCDNMLSMQPADVFI   450
 451  WDVDFEITRKNFRKAHSKDTNEKIRLSHHSFKIKNRQKVMKLSVRSGRWL   500
 501  QQFINSVQVAQGLTAWCEIHRFDSFAPVRTNVAVQWMVDARDHMWNVSRA   550
 551  IKNAKRCIMIHGWWLSPELQMRRPYSMAHKWRIDRILNEKAHEGVMVYIM   600
 601  IYRNIDATIPIDSFHTKEHLQSLHPNIYVIRSPSHFRQNALFWAHHEKLV   650
 651  VVDDAITFIGGIDLCFGRYDTPQHILYDDKPVADKTGLCEQTWRGKDYSN   700
 701  ARVHDFFDLTEPYKDMYDRLAVPRMGWHDVSMCIIGQPARDAARHFVQRW   750
 751  NYLIQCKKPARKTPLLIPPPDFTTDQLTDSQLTGTCEVQVLRSAGLWSLG   800
 801  LVDTVEQSIQNAYVTCIEKSEHFIYIENQFFVTSTTCEGTTIENRVGDAL   850
 851  VERIIRAHKNNEKWRGVIMIPLLPGFEGQIDLQEGGSLRLIVECQYRSIC   900
 901  HGEHSIFGRLNAKGIDGSKYLRFYGLRGWAHLGENHELVTEMIYVHAKIL   950
 951  IADDRVAVIGSANINERSLLGNRDSEIAAVIRDTLTIDSKMDGKPYKVGK  1000
1001  FAHTLRKRLMREHLGLETDVLEQREYNMDGLDRDTEWKRVEVWTPDEGNA  1050
1051  INGSAYTAEELKMKYRSQSQFTTTPDILRKAEKSMKKLDQRVSLIPSSIE  1100
1101  FNIKTQKDKVEFEKNYEKSKKGPDVIANALVGGIPLSLKTKEDSLYELSK  1150
1151  FSQCGEDQRPMVLKDPDHLVPEPSRPHCGNGLVFYDDIPLLEVNPISGET  1200
1201  IPKFDASSFEDPVCDEFFEDIWSKVASNNTTIYRHIFRCVPDDEMLTWES  1250
1251  YNEWKKYGKRFKEEQARWRQEELSNLHETHEKSENDPKNPKAGSQGSGNT  1300
1301  SASEDSKTEKPKTRTNNGLQVPDKRVVYDLLRGIRGQLVELPLKWMSTES  1350
1351  NARNWLSSIDKIPPLEIYD                                 1369

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.