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

NucPred

Fetching Q9Y2H9 from www.uniprot.org...

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

   1  MSDSLWTALSNFSMPSFPGGSMFRRTKSCRTSNRKSLILTSTSPTLPRPH    50
  51  SPLPGHLGSSPLDSPRNFSPNTPAHFSFASSRRADGRRWSLASLPSSGYG   100
 101  TNTPSSTVSSSCSSQERLHQLPYQPTVDELHFLSKHFGSTESITDEDGGR   150
 151  RSPAVRPRSRSLSPGRSPSSYDNEIVMMNHVYKERFPKATAQMEEKLRDF   200
 201  TRAYEPDSVLPLADGVLSFIHHQIIELARDCLTKSRDGLITTVYFYELQE   250
 251  NLEKLLQDAYERSESLEVAFVTQLVKKLLIIISRPARLLECLEFNPEEFY   300
 301  HLLEAAEGHAKEGHLVKTDIPRYIIRQLGLTRDPFPDVVHLEEQDSGGSN   350
 351  TPEQDDLSEGRSSKAKKPPGENDFDTIKLISNGAYGAVYLVRHRDTRQRF   400
 401  AMKKINKQNLILRNQIQQAFVERDILTFAENPFVVGMFCSFETRRHLCMV   450
 451  MEYVEGGDCATLLKNIGALPVEMARMYFAETVLALEYLHNYGIVHRDLKP   500
 501  DNLLITSMGHIKLTDFGLSKMGLMSLTTNLYEGHIEKDAREFLDKQVCGT   550
 551  PEYIAPEVILRQGYGKPVDWWAMGIILYEFLVGCVPFFGDTPEELFGQVI   600
 601  SDDILWPEGDEALPTEAQLLISSLLQTNPLVRLGAGGAFEVKQHSFFRDL   650
 651  DWTGLLRQKAEFIPHLESEDDTSYFDTRSDRYHHVNSYDEDDTTEEEPVE   700
 701  IRQFSSCSPRFSKVYSSMEQLSQHEPKTPVAAAGSSKREPSTKGPEEKVA   750
 751  GKREGLGGLTLREKTWRGGSPEIKRFSASEASFLEGEASPPLGARRRFSA   800
 801  LLEPSRFSAPQEDEDEARLRRPPRPSSDPAGSLDARAPKEETQGEGTSSA   850
 851  GDSEATDRPRPGDLCPPSKDGDASGPRATNDLVLRRARHQQMSGDVAVEK   900
 901  RPSRTGGKVIKSASATALSVMIPAVDPHGSSPLASPMSPRSLSSNPSSRD   950
 951  SSPSRDYSPAVSGLRSPITIQRSGKKYGFTLRAIRVYMGDTDVYSVHHIV  1000
1001  WHVEEGGPAQEAGLCAGDLITHVNGEPVHGMVHPEVVELILKSGNKVAVT  1050
1051  TTPFENTSIRIGPARRSSYKAKMARRNKRPSAKEGQESKKRSSLFRKITK  1100
1101  QSNLLHTSRSLSSLNRSLSSSDSLPGSPTHGLPARSPTHSYRSTPDSAYL  1150
1151  GASSQSSSPASSTPNSPASSASHHIRPSTLHGLSPKLHRQYRSARCKSAG  1200
1201  NIPLSPLAHTPSPTQASPPPLPGHTVGSSHTTQSFPAKLHSSPPVVRPRP  1250
1251  KSAEPPRSPLLKRVQSAEKLGASLSADKKGALRKHSLEVGHPDFRKDFHG  1300
1301  ELALHSLAESDGETPPVEGLGAPRQVAVRRLGRQESPLSLGADPLLPEGA  1350
1351  SRPPVSSKEKESPGGAEACTPPRATTPGGRTLERDVGCTRHQSVQTEDGT  1400
1401  GGMARAVAKAALSPVQEHETGRRSSSGEAGTPLVPIVVEPARPGAKAVVP  1450
1451  QPLGADSKGLQEPAPLAPSVPEAPRGRERWVLEVVEERTTLSGPRSKPAS  1500
1501  PKLSPEPQTPSLAPAKCSAPSSAVTPVPPASLLGSGTKPQVGLTSRCPAE  1550
1551  AVPPAGLTKKGVSSPAPPGP                                1570

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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