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

NucPred

Fetching P33202 from www.uniprot.org...

The NucPred score for your sequence is 0.71 (see score help below)

   1  MSENNSHNLDEHESHSENSDYMMDTQVEDDYDEDGHVQGEYSYYPDEDED    50
  51  EHMLSSVGSFEADDGEDDDNDYHHEDDSGLLYGYHRTQNGSDEDRNEEED   100
 101  GLERSHDNNEFGSNPLHLPDILETFAQRLEQRRQTSEGLGQHPVGRTLPE   150
 151  ILSMIGGRMERSAESSARNERISKLIENTGNASEDPYIAMESLKELSENI   200
 201  LMMNQMVVDRIIPMETLIGNIAAILSDKILREELELQMQACRCMYNLFEV   250
 251  CPESISIAVDEHVIPILQGKLVEISYIDLAEQVLETVEYISRVHGRDILK   300
 301  TGQLSIYVQFFDFLTIHAQRKAIAIVSNACSSIRTDDFKTIVEVLPTLKP   350
 351  IFSNATDQPILTRLVNAMYGICGALHGVDKFETLFSLDLIERIVQLVSIQ   400
 401  DTPLENKLKCLDILTVLAMSSDVLSRELREKTDIVDMATRSFQHYSKSPN   450
 451  AGLHETLIYVPNSLLISISRFIVVLFPPEDERILSADKYTGNSDRGVISN   500
 501  QEKFDSLVQCLIPILVEIYTNAADFDVRRYVLIALLRVVSCINNSTAKAI   550
 551  NDQLIKLIGSILAQKETASNANGTYSSEAGTLLVGGLSLLDLICKKFSEL   600
 601  FFPSIKREGIFDLVKDLSVDFNNIDLKEDGNENISLSDEEGDLHSSIEEC   650
 651  DEGDEEYDYEFTDMEIPDSVKPKKISIHIFRTLSLAYIKNKGVNLVNRVL   700
 701  SQMNVEQEAITEELHQIEGVVSILENPSTPDKTEEDWKGIWSVLKKCIFH   750
 751  EDFDVSGFEFTSTGLASSITKRITSSTVSHFILAKSFLEVFEDCIDRFLE   800
 801  ILQSALTRLENFSIVDCGLHDGGGVSSLAKEIKIKLVYDGDASKDNIGTD   850
 851  LSSTIVSVHCIASFTSLNEFLRHRMVRMRFLNSLIPNLTSSSTEADREEE   900
 901  ENCLDHMRKKNFDFFYDNEKVDMESTVFGVIFNTFVRRNRDLKTLWDDTH   950
 951  TIKFCKSLEGNNRESEAAEEANEGKKLRDFYKKREFAQVDTGSSADILTL  1000
1001  LDFLHSCGVKSDSFINSKLSAKLARQLDEPLVVASGALPDWSLFLTRRFP  1050
1051  FLFPFDTRMLFLQCTSFGYGRLIQLWKNKSKGSKDLRNDEALQQLGRITR  1100
1101  RKLRISRKTIFATGLKILSKYGSSPDVLEIEYQEEAGTGLGPTLEFYSVV  1150
1151  SKYFARKSLNMWRCNSYSYRSEMDVDTTDDYITTLLFPEPLNPFSNNEKV  1200
1201  IELFGYLGTFVARSLLDNRILDFRFSKVFFELLHRMSTPNVTTVPSDVET  1250
1251  CLLMIELVDPLLAKSLKYIVANKDDNMTLESLSLTFTVPGNDDIELIPGG  1300
1301  CNKSLNSSNVEEYIHGVIDQILGKGIEKQLKAFIEGFSKVFSYERMLILF  1350
1351  PDELVDIFGRVEEDWSMATLYTNLNAEHGYTMDSSIIHDFISIISAFGKH  1400
1401  ERRLFLQFLTGSPKLPIGGFKSLNPKFTVVLKHAEDGLTADEYLPSVMTC  1450
1451  ANYLKLPKYTSKDIMRSRLCQAIEEGAGAFLLS                   1483

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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