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

NucPred

Fetching Q61602 from www.uniprot.org...

The NucPred score for your sequence is 0.92 (see score help below)

   1  MEAQAHSSTATERKKAENSIGKCPTRTDVSEKAVASSTTSNEDESPGQIY    50
  51  HRERRNAITMQPQSVQGLNKISEEPSTSSDERASLIKKEIHGSLPHLAEP   100
 101  SLPYRGTVFAMDPRNGYMEPHYHPPHLFPAFHPPVPIDARHHEGRYHYDP   150
 151  SPIPPLHVPSALSSSPTYPDLPFIRISPHRNPTAASESPFSPPHPYINPY   200
 201  MDYIRSLHSSPSLSMISAARGLSPTDAPHAGVSPAEYYHQMALLTGQRSP   250
 251  YADILPSAATAGAGAIHMEYLHAMDSTRFPSPRLSARPSRKRTLSISPLS   300
 301  DHSFDLQTMIRTSPNSLVTILNNSRSSSSASGSYGHLSASAISPALSFTY   350
 351  PSAPVSLHMHQQILSRQQSLGSAFGHSPPLIHPAPTFPTQRPIPGIPTVL   400
 401  NPVQVSSGPSESSQSKPTSESAVSSTGDPMHNKRSKIKPDEDLPSPGSRG   450
 451  QQEQPEGTTLVKEEADKDESKQEPEVIYETNCHWEGCTREFDTQDQLVHH   500
 501  INNDHIHGEKKEFVCRWLDCSREQKPFKAQYMLVVHMRRHTGEKPHKCTF   550
 551  EGCTKAYSRLENLKTHLRSHTGEKPYVCEHEGCNKAFSNASDRAKHQNRT   600
 601  HSNEKPYVCKIPGCTKRYTDPSSLRKHVKTVHGPEAHVTKKQRGDMHPRP   650
 651  PPPRDSGSHSQSRSPGRPTQGAFGEQKELSNTTSKREECLQVKTVKAEKP   700
 701  MTSQPSPGGQSSCSSQQSPISNYSNSGLELPLTDGGSVADLSAIDETPIM   750
 751  DSTISTATTALALQARRNPAGTKWMEHIKLERLKQVNGMFPRLNPILPSK   800
 801  APAVSPLIGNGTQSNNNYSSGGPGTLLPSRSDLSGVDFTVLNTLNRRDSN   850
 851  TSTISSAYLSSRRSSGISPCFSSRRSSEASQAEGRPQNVSVADSYDPIST   900
 901  DASRRSSEASQGDGLPSLLSLTPVQQYRLKAKYAAATGGPPPTPLPHMER   950
 951  LSLKTKMALLGEGRDSGVTLPPVHPPRRCSDGGGHTYRGRHLMPHDALAN  1000
1001  SVRRASDPVRTVSENMSLARVQRFSSLNSFNPPNLPPSVEKRSLVLQNYT  1050
1051  RQESSQPRYFQASPCPPSITENVALEALTMDADANLNDEDLLPDDVVQYL  1100
1101  NSQNQTGYGQQLQSGISEDSKVAHEPEDLDLAGLPDSHVGQEYPALEQPC  1150
1151  SEGSKTDLPIQWNEVSSGTSDLSSSKLKCGQQRPSAQQPRGFGLYNNMVV  1200
1201  HPHNLWKVGTGPAGGYQTLGENSSTYNGPEHFAIHSGDGLGTNGNTFHEQ  1250
1251  PFKTQQYGSQLNRQPLTSSALDHACGTGIQGSKLKGNSLQENGGLLDFSL  1300
1301  SVAPNELAGNTVNGMQTQDQMGQGYIAHQLLSGSMQHQGPSRPGQQVLGQ  1350
1351  VGATSHINIYQGTESCLPGTQDNSSQPSSMAAIRGYQPCASYGGNRRQAM  1400
1401  PRGNLTLQQGQLSDMSQSSRVNSIKMEAQGQSQQLCSTVQNYSGQFYDQT  1450
1451  MGFSQQDRKAGSFSLSDANCLLQGNGTENSELLSPGANQVTSTVDSFESH  1500
1501  DLEGVQIDFDAIIDDGDHTSLMSGALSPSIIQNLSHSSSRLTTPRASLPF  1550
1551  PSLSMGTTNMAIGDMSSLLTSLAEESKFLAVMQ                   1583

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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