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

NucPred

Fetching Q5DX34 from www.uniprot.org...

The NucPred score for your sequence is 0.65 (see score help below)

   1  MFFKRSTNSRKTSANSSSDTSTSSESLLLPLLNNTKAGARSQKGSVHRQS    50
  51  GKKARRKMMENPYVCSLELDELSADDSIIDYSVFSDDSFLLILLLTSKGD   100
 101  VQAYLETSRDTKPRKNVVNIKTACSLNVSPVTVCIGSQAAFAIFGLADGN   150
 151  LLVTPIRLLIDVTWGGSSWATTTVIDLSLPTVDPCLATPTCTKCFVSNFP   200
 201  PCTMAVVANKAGNILLVDLHLRKCVSELKAPQSLHQIDILLDENSIELLV   250
 251  TGFTGAQWIIPIERSGKGFREVLTTCVPSDLTVLEPATMQFFAADSCGVV   300
 301  ALDTTESIVEVYNTFHSLAHSSKRTFKVPPETWMVHAGDNMLFTVSNDNE   350
 351  IRSALHFGFMSSRLEYTLVRTSTNWRPLGIVAMPSRPHKLAGIFVVNERG   400
 401  LVRVEQSTALNLTKIASEFFFRLSPLQLNSKSVAQVANACRIDTAEFQSA   450
 451  LIPNLLSTRKNRQLTNKELSQIYSIAKAINLSMSDLLKAFENESIGEQLL   500
 501  PEVLNTIQTNPAKHDNLMQRVVEMFVKRSLSAEGNMDKIREYDAELSNFL   550
 551  ARHEHLHKGSVDCAKAGMWKCTQTLVRRDVHETKSIDTSTEVLLYIIKNR   600
 601  LQIWNEANSTDRLQIMSLVCHLDWSKLADADGARVCAILSAWQRDISLPS   650
 651  YHEMCLRIAITNSDRFPRPCQILSLVSSIHILSEKKISNHANLPNFLPLA   700
 701  GGNNCGATITEDDRLMIWGNFTNAQQRMEMPQMNAKSKRSDSVTNGAPTL   750
 751  PPPAPKPEQHLPRVLEYPGGRPRAIACGAEHILVLSSSGQLSAWGGNRFG   800
 801  QCGVGHSFRIANLHQVDGDWPAIEKIACGQFHSAFICSDGSLWTFGWGVW   850
 851  GQLGHGGRNNSNQLVPTRVNGLICKVTQIACGRAHTVVLTDTGRVLVCGS   900
 901  GSYGQMGVDDDIKKVFAFTPLPLGPLRVRDIATHYYHSICITEDNRVFEW   950
 951  GRNPQELKMRMFVMKKIRSAQLKNTEDPSSPSPSTNGSTPRVNLNLPAEI  1000
1001  PREDLGLREVKHFLDGNIVSVACGLSHSALITSEGTLYTWGKGLDYQLGH  1050
1051  GNKNERMEPHQVFEPNGAKWVNVSLGNNHTIASTDDGSVFAWGKNDFGQC  1100
1101  GVLTKKNGNSADVTKKFFFQARDGRRFMPNVDESQFVQKPGLIPDVRVRN  1150
1151  LNEDGNEGVDKEEIVDRLKASDVNVVQAVSKHLYSPIEGKCNGSIIEDEP  1200
1201  RNGKIQKQNKYDGEDGPLCTTTALVHLIAGDVKRAIRMIEWLKTDSSTCE  1250
1251  KSLMVLSSLVWEVMANHEDVQSREALSAAFRHVPMSDSMRKGKQIAQLWP  1300
1301  AVWNDERVQSSLSIDEKIAMLDGFTSASKPVSCPTIPSSSLEVSSKIRVY  1350
1351  AQCAHAEPAAVGSPPECSTCLDEWTEKVRHTLGTQL                1386

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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