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

NucPred

Fetching Q9URU2 from www.uniprot.org...

The NucPred score for your sequence is 0.83 (see score help below)

   1  MFNDQSKTTSSVKGICATTDNNHGNLKKTNSTPFRKNYLLNGRTKLKLEN    50
  51  FAYNASTEISSPKISEKKHSSLPIKRKNTFNESSTSFSPFTKAHKEITDD   100
 101  LKPDKSFTRKSDLNSQDMPVCFQETSKDLCRSSSTQHLLDHQTTDSTIID   150
 151  MKPVSTNSKSDVFTLYTDETVLLRRCASDNKPLINNNLSSSNVSENQSRS   200
 201  FGSYDEVKNQGNNLHKVPSLVSIIRNARSSEQSRIAANSSCLLKGSDTEI   250
 251  DEDDFALEAEDLAALDSLERQYSQLPNSTVTASAKDIEKTAKVNHVGGDL   300
 301  QSYCSATKASDATINEEPVNLALDKACNSLPDINSDFIDDWDDSCDGCTP   350
 351  GELCEFSSEYTVLEVHEDFIFHEGNHFRQLKLILEANDILHQLFLRGDWT   400
 401  ETSIFVGDSIRVEATFDKDNTAIVDNDKGLIIIHPKILMSATAVASSFPC   450
 451  LRKAVISDRVGIYGPPTKAMVTGNILHDFFQHALYRGIDALENVDINLET   500
 501  SIKTYISDIYFADLSLDEIREELDARLPLLKSIVERYLISKKNDNNNESI   550
 551  HISRLLDIEESIWSPRFGLKGNIDATVEVVLTEKPESSSTLTLPLELKTG   600
 601  RYVDNISHFAQSLLYTLLISDRYGINTNQALLCYLENSTIKNLVASNSQL   650
 651  RGLIMTRNSLAQHNFRRSLPEMISNRKICDHCSLVSECLFFQKMSDKGVA   700
 701  NSNGLTESWNEWMREVKDEDLEFYKKWEKLLNQEERLLLLKRGDVLTFDT   750
 751  EELEAYGKTLYPLYITKEDIVCLEIDDRVFHYKFAFLNDNGYPRNFLHSG   800
 801  FSVGERVFISDEHGHWSLAKGHIVHIQDSCIEVRTRHRLHIPWLKMPNFD   850
 851  FKKNQVFFGNYEDSKLSFIGSNHTRYRIDKDEFSSGIASIRGTLMSSVLP   900
 901  DAPLIIRDMIIRLKPPKFCNSALIDPEFLKCLNEDQITALKKCHAAEHYS   950
 951  LILGMPGTGKTTTISSLIRSLLAKKKKILLTSFTHLAVDNILIKLKGCDS  1000
1001  TIVRLGSPHKIHPLVKEFCLTEGTTFDDLASLKHFYEDPQIVACSSLGVY  1050
1051  HSIFNKRKFDYCIIDEASQIPLPICLGPLQLAEKFVLVGDHYQLPPLVKN  1100
1101  SRTSKDGLSLSLFKLLSEKHPEAVTTLRLQYRMNEDINSLSSELIYGGNL  1150
1151  VCGSKTISQKKLILPKAHLSDGLPDSSSSLHWVNKLINPSHSVIFFNTDD  1200
1201  ILGVESKTNNILENHTEAFLIEQAVSSFLERGVKQSSIGIISIYKSQVEL  1250
1251  LSKNLKSFTEIEINTVDRYQGRDKDIILISFVRSNSKNLVGELLRDWHRL  1300
1301  NVALSRAKVKCIMFGSLSTLSSSNIVSHLLKLLEKNKWIFTLNENDIATK  1350
1351  FDENSSPIKDCSQVATTNNAKVIIRKNQRFFNSDNLCEKAILPQLEF     1397

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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