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

NucPred

Fetching Q12767 from www.uniprot.org...

The NucPred score for your sequence is 0.82 (see score help below)

   1  MDLKEKHLGEPPSALGLSTRKALSVLKEQLEAVLEGHLRERKKCLTWKEV    50
  51  WRSSFLHHSNRCSCFHWPGASLMLLAVLLLLGCCGGQPAGSRGVGLVNAS   100
 101  ALFLLLLLNLVLIGRQDRLKRREVERRLRGIIDQIQDALRDGREIQWPSA   150
 151  MYPDLHMPFAPSWSLHWAYRDGHLVNLPVSLLVEGDIIALRPGQESFASL   200
 201  RGIKDDEHIVLEPGDLFPPFSPPPSPRGEVERGPQSPQQHRLFRVLETPV   250
 251  IDNIRWCLDMALSRPVTALDNERFTVQSVMLHYAVPVVLAGFLITNALRF   300
 301  IFSAPGVTSWQYTLLQLQVNGVLPILPLLFPVLWVLATACGEARVLAQMS   350
 351  KASPSSLLAKFSEDTLSSYTEAVSSQEMLRCIWGHFLRVLGGTSPTLSHS   400
 401  SSLLHSLGSVTVLCCVDKQGILSWPNPSPETVLFFSGKVEPPHSSHEDLT   450
 451  DGLSTRSFCHPEPHERDALLAGSLNNTLHLSNEQERGDWPGEAPKPPEPY   500
 501  SHHKAHGRSKHPSGSNVSFSRDTEGGEEEPSKTQPGMESDPYEAEDFVCD   550
 551  YHLEMLSLSQDQQNPSCIQFDDSNWQLHLTSLKPLGLNVLLNLCDASVTE   600
 601  RLCRFSDHLCNIALQESHSAVLPVHVPWGLCELARLIGFTPGAKELFKQE   650
 651  NHLALYRLPSAETMKETSLGRLSCVTKRRPPLSHMISLFIKDTTTSTEQM   700
 701  LSHGTADVVLEACTDFWDGADIYPLSGSDRKKVLDFYQRACLSGYCSAFA   750
 751  YKPMNCALSSQLNGKCIELVQVPGQSSIFTMCELPSTIPIKQNARRSSWS   800
 801  SDEGIGEVLEKEDCMQALSGQIFMGMVSSQYQARLDIVRLIDGLVNACIR   850
 851  FVYFSLEDELKSKVFAEKMGLETGWNCHISLTPNGDMPGSEIPPSSPSHA   900
 901  GSLHDDLNQVSRDDAEGLLLMEEEGHSDLISFQPTDSDIPSFLEDSNRAK   950
 951  LPRGIHQVRPHLQNIDNVPLLVPLFTDCTPETMCEMIKIMQEYGEVTCCL  1000
1001  GSSANLRNSCLFLQSDISIALDPLYPSRCSWETFGYATSISMAQASDGLS  1050
1051  PLQLSGQLNSLPCSLTFRQEETISIIRLIEQARHATYGIRKCFLFLLQCQ  1100
1101  LTLVVIQFLSCLVQLPPLLSTTDILWLSCFCYPLLSISLLGKPPHSSIMS  1150
1151  MATGKNLQSIPKKTQHYFLLCFLLKFSLTISSCLICFGFTLQSFCDSSRD  1200
1201  RNLTNCSSVMLPSNDDRAPAWFEDFANGLLSAQKLTAALIVLHTVFISIT  1250
1251  HVHRTKPLWRKSPLTNLWWAVTVPVVLLGQVVQTAVDLQLWTHRDSHVHF  1300
1301  GLEDVPLLTWLLGCLSLVLVVVTNEIVKLHEIRVRVRYQKRQKLQFETKL  1350
1351  GMNSPF                                              1356

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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