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

NucPred

Fetching Q98893 from www.uniprot.org...

The NucPred score for your sequence is 0.33 (see score help below)

   1  MRVLVLALTVALVAGNQVSYAPEFAPGKTYEYKYEGYILGGLPEEGLAKA    50
  51  GVKIQSKVLIGAAGPDSYILKLEDPVISGYSGIWPKEVFHPATKLTSALS   100
 101  AQLLTPVKFEYANGVIGKVFAPPGISTNVLNVFRGLLNMFQMNIKKTQNV   150
 151  YDLQETGVKGVCKTHYILHEDSKADRLHLTKTTDLNHCTDSIHMDVGMAG   200
 201  YTEKCAECMARGKTLSGAISVNYIMKPSASGTLILEATATELLQYSPVNI   250
 251  VNGAVQMEAKQTVTFVDIRKTPLEPLKADYIPRGSLKYELGTEFLQTPIQ   300
 301  LLRITNVEAQIVESLNNLVSLNMGHAHEDSPLKFIELIQLLRVAKYESIE   350
 351  ALWSQFKTKIDHRHWLLSSIPAIGTHVALKFIKEKIVAGEVTAAEAAQAI   400
 401  MSSTHLVKADLEAIKLQEGLAVTPNIRENAGLRELVMLGFGIMVHKYCVE   450
 451  NPSCPSELVRPVHDIIAKALEKRDNDELSLALKVLGNAGHPSSLKPIMKL   500
 501  LPGFGSSASELELRVHIDATLALRKIGKREPKMIQDVALQLFMDRTLDPE   550
 551  LRMVAVVVLFDTKLPMGLITTLAQSLLKEPNLQVLSFVYSYMKAFTKTTT   600
 601  PDHSTVAAACNVAIRILSPRFERLSYRYSRAFHYDHYHNPWMLGAAASAF   650
 651  YINDAATVLPKNIMAKARVYLSGVSVDVLEFGARAEGVQEALLKARDVPE   700
 701  SADRLTKMKQALKALTEWRANPSRQPLGSLYVKVLGQDVAFANIDKEMVE   750
 751  KIIEFATGPEIRTRGKKALDALLSGYSMKYSKPMSAIEVRHIFPTSLGLP   800
 801  MELSLYTAAVTAASVEVQATISPPLPEDFHPAHLLKSDISMKASVTPSVS   850
 851  LHTYGVMGVNSPFIQASVLSRAKDHAALPKKMEARLDIVKGYFSYQFLPV   900
 901  EGVKTIASARLETVAIARDVEGLAAAKVTPVVPYEPIVSKNATLNLSQMS   950
 951  YYLNDSISASSELLPFSLQRQTGKNKIPKPIVKKMCATTYTYGIEGCVDI  1000
1001  WSRNATFLRNTPIYAIIGNHSLLVNVTPAAGPSIERIEIEVQFGEQAAEK  1050
1051  ILKEVYLNEEEEVLEDKNVLMKLKKILSPGLKNSTKASSSSSGSSRSSRS  1100
1101  RSSSSSSSSSSSSSSRSSSSSSRSSSSLRRNSKMLDLADPLNITSKRSSS  1150
1151  SSSSSSSSSSSSSSSSSSSKTKWQLHERNFTKDHIHQHSVSKERLNSKSS  1200
1201  ASSFESIYNKITYLSNIVSPVVTVLVRAIRADHKNQGYQIAVYYDKLTTR  1250
1251  VQIIVANLTEDDNWRICSDSMMLSHHKVMTRVTWGIGCKQYNTTIVAETG  1300
1301  RVEKEPAVRVKLAWARLPTYIRDYARRVSRYISRVAEDNGVNRTKVASKP  1350
1351  KEIKLTVAVANETSLNVTLNTPKNTFFKLGWVLPFYLPINNTAAELQAFQ  1400
1401  GRWMDQVTYMLTKSAAAECTVVEDTVVTFNNRKYKTETPHSCHQVLAQDC  1450
1451  TSEIKFIVLLKRDQTAERNEISIKIENIDVDMYPKDNAVVVKVNGVEIPL  1500
1501  TNLPYQHPTGNIQIRQREEGISLHAPSHGLQEVFLSLNKVQVKVVDWMRG  1550
1551  QTCGLCGKADGEVRQEYSTPNERVSRNATSFAHSWVLPAKSCRDASECYM  1600
1601  QLESVKLEKQISLEGEESKCYSVEPVWRCLPGCAPVRTTSVTVGLPCVSL  1650
1651  DSNLNRSDSLSSIYQKSVDVSETAESHLACRCTPQCA               1687

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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