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

NucPred

Fetching Q15788 from www.uniprot.org...

The NucPred score for your sequence is 0.94 (see score help below)

   1  MSGLGDSSSDPANPDSHKRKGSPCDTLASSTEKRRREQENKYLEELAELL    50
  51  SANISDIDSLSVKPDKCKILKKTVDQIQLMKRMEQEKSTTDDDVQKSDIS   100
 101  SSSQGVIEKESLGPLLLEALDGFFFVVNCEGRIVFVSENVTSYLGYNQEE   150
 151  LMNTSVYSILHVGDHAEFVKNLLPKSLVNGVPWPQEATRRNSHTFNCRML   200
 201  IHPPDEPGTENQEACQRYEVMQCFTVSQPKSIQEDGEDFQSCLICIARRL   250
 251  PRPPAITGVESFMTKQDTTGKIISIDTSSLRAAGRTGWEDLVRKCIYAFF   300
 301  QPQGREPSYARQLFQEVMTRGTASSPSYRFILNDGTMLSAHTKCKLCYPQ   350
 351  SPDMQPFIMGIHIIDREHSGLSPQDDTNSGMSIPRVNPSVNPSISPAHGV   400
 401  ARSSTLPPSNSNMVSTRINRQQSSDLHSSSHSNSSNSQGSFGCSPGSQIV   450
 451  ANVALNQGQASSQSSNPSLNLNNSPMEGTGISLAQFMSPRRQVTSGLATR   500
 501  PRMPNNSFPPNISTLSSPVGMTSSACNNNNRSYSNIPVTSLQGMNEGPNN   550
 551  SVGFSASSPVLRQMSSQNSPSRLNIQPAKAESKDNKEIASILNEMIQSDN   600
 601  SSSDGKPLDSGLLHNNDRLSDGDSKYSQTSHKLVQLLTTTAEQQLRHADI   650
 651  DTSCKDVLSCTGTSNSASANSSGGSCPSSHSSLTERHKILHRLLQEGSPS   700
 701  DITTLSVEPDKKDSASTSVSVTGQVQGNSSIKLELDASKKKESKDHQLLR   750
 751  YLLDKDEKDLRSTPNLSLDDVKVKVEKKEQMDPCNTNPTPMTKPTPEEIK   800
 801  LEAQSQFTADLDQFDQLLPTLEKAAQLPGLCETDRMDGAVTSVTIKSEIL   850
 851  PASLQSATARPTSRLNRLPELELEAIDNQFGQPGTGDQIPWTNNTVTAIN   900
 901  QSKSEDQCISSQLDELLCPPTTVEGRNDEKALLEQLVSFLSGKDETELAE   950
 951  LDRALGIDKLVQGGGLDVLSERFPPQQATPPLIMEERPNLYSQPYSSPSP  1000
1001  TANLPSPFQGMVRQKPSLGTMPVQVTPPRGAFSPGMGMQPRQTLNRPPAA  1050
1051  PNQLRLQLQQRLQGQQQLIHQNRQAILNQFAATAPVGINMRSGMQQQITP  1100
1101  QPPLNAQMLAQRQRELYSQQHRQRQLIQQQRAMLMRQQSFGNNLPPSSGL  1150
1151  PVQMGNPRLPQGAPQQFPYPPNYGTNPGTPPASTSPFSQLAANPEASLAN  1200
1201  RNSMVSRGMTGNIGGQFGTGINPQMQQNVFQYPGAGMVPQGEANFAPSLS  1250
1251  PGSSMVPMPIPPPQSSLLQQTPPASGYQSPDMKAWQQGAIGNNNVFSQAV  1300
1301  QNQPTPAQPGVYNNMSITVSMAGGNTNVQNMNPMMAQMQMSSLQMPGMNT  1350
1351  VCPEQINDPALRHTGLYCNQLSSTDLLKTEADGTQQVQQVQVFADVQCTV  1400
1401  NLVGGDPYLNQPGPLGTQKPTSGPQTPQAQQKSLLQQLLTE           1441

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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