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

NucPred

Fetching Q43155 from www.uniprot.org...

The NucPred score for your sequence is 0.29 (see score help below)

   1  MALQSAPKLLYSSPSPSVFSANERRVAFSDFVGLSKKRSRRRRIAGTFRN    50
  51  FPALSAVSSAIKAVVDVDRAHHSTDSGSPTVSTSSHPLDQQVVNLEDILA   100
 101  ERGACGVGFIANLDNKGSFQIVKDALTALGCMEHRGGCGSDNDSGDGSGV   150
 151  MTAIPWDLFNDWGKDQGIGPFDRSHTGVGMVFLPKDDLLAEEAKKVVLDT   200
 201  FAQEGIEVIGWRSVPTNVSVVGRNAKETMPNIQQVFVRIIKEDSTDDIER   250
 251  ELYICRKLIERAASSHTWASELYFCSLSNQTIIYKGMLRSEVLGMFYYDL   300
 301  QNERYTSPFAIYHRRYSTNTSPRWPLAQPMRFLGHNGEINTIQGNLNWMR   350
 351  SREPSIQSPVWRGRENEIRPYGNPKASDSANLDSAAELLIRSGRTPEEAL   400
 401  MILVPEAYKNHPTLMIKYPEAVDFYDYYKGQMETWDGPALLLFSDGKTVG   450
 451  ACLDRNGLRPARYWRTVDNVVYVASEVGVLPMDESKVTMKGRLGPGMMIS   500
 501  VDLSSGQVYENTEVKKRVASSNPYGKWVKENLRSLKAVNFLSRALLENDT   550
 551  ILRNQQAFGYSSEDVQMVIESMASQGKEPTFCMGDDIPLAVMSQKPHMLY   600
 601  DYFKQRFAQVTNPAIDPLREGLVMSLEVNIGKRGNILEVGPENASQVILP   650
 651  SPVLNEGELEALVNDPLLKAQMLPIFFDIRKGVEGTLEKRLNRLCEAADE   700
 701  AVRNGSQMLVLSDRSEELEPTRPAIPILLAVGAVHQHLIQNGLRMYTSIV   750
 751  VDTAQCFSTHQFACLIGYGASAICPYLALETCRQWRLSNKTVNLMRTGKI   800
 801  PTVTIEQAQKNFCKAVKSGLLKILSKMGISLLSSYCGAQIFEIYGLGKDV   850
 851  VDIAFQGSVSKMGGLTLDELARETLSFWVKAFSEDTAKRLENFGFIQFRP   900
 901  GGEYHVNNPEMSKLLHKAVRNKSESAYAVYQQHLANRPVSVLRDLLEFKS   950
 951  DRAPISVGKVEPATSIVERFCTGGMSLGAISRETHEAIAIAMNRLGGKSN  1000
1001  SGEGGEDPIRWRPLTDVVDGYSSTLPHLKGLQNGDTATSAIKQVASGRFG  1050
1051  VTPTFLVNADQIEIKIAQGAKPGEGGQLPGKKVSAYIARLRNSKPGVPLI  1100
1101  SPPPHHDIYSIEDLAQLIYDLHQINPKEKVSVKLVAEAGIGTVASGVAKG  1150
1151  NADIIQVSGHDGGTGASPISSIKHAGGPWELGLSETHQTLISNGLRERVI  1200
1201  LRVDGGLKCGVDVMMAAAMGADEYGFGSLAMIATGCVMARICHTNNCPVG  1250
1251  VASQREELRARFPGVPGDLVNFFLYVAEEVRGILAQLGFEKLDDIIGRTD  1300
1301  ILKPRDISLMKTQHLDLSYILASAGLPTMSSTAIRKQEVHTNGPVLDDQI  1350
1351  LSDPEIIDAIENEKIVNKTVKIFNVDRAVCGRIAGVIAKKYGDTGFAGQL  1400
1401  NLTFEGSAGQSFAVFLTPGMNIRLVGESNDYVGKGMAGGELIVTPAENPG  1450
1451  FRPEDATIVGNTCLYGATGGQIFVRGKAGERFAVRNSLAEAVVEGTGDHC  1500
1501  CEYMTGGCVVILGKVGRNVAAGMTGGLAYILDEDDTLIPKVNKEIVKIQR  1550
1551  VTAPVGQMQLKNLIEAHVEKTGSSKGASILKDWDKYLPLFWQLVPPSEED  1600
1601  TPEASAMFEQMTSEGASLQSA                               1621

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.