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

NucPred

Fetching Q9T0P4 from www.uniprot.org...

The NucPred score for your sequence is 0.29 (see score help below)

   1  MALQSPGATGASSSVSRLLSSAKLSSTKTIFSVDFVRSYCISKGTKRRNE    50
  51  LSGFRGYSPLLKSSLRSPFSVKAILNSDRAAGDASSSFSDLKPQVAYLED   100
 101  IISERGACGVGFIANLENKATHKIVNDALIALGCMEHRGGCGSDNTSGDG   150
 151  SGLMTSIPWDLFNEWAEKQGIASFDRTHTGVGMLFLPRDDNIRKEAKKVI   200
 201  TSIFEKEGLEVLGWRDVPVEASIVGHNAKQTMPNTEQVFVRIVKDDKVDD   250
 251  VERELYICRKLIERAVASESWASELYFSSLSNQTIVYKGMLRSEVLGLFY   300
 301  PDLQNDLYKSPFAIYHRRFSTNTSPRWHLAQPMRFLGHNGEINTIQGNLN   350
 351  WMTSREASLRSPVWHGRENDIRPISNPKASDSANLDSAAELLIRSGRTPE   400
 401  ESLMILVPEAYKNHPTLMIKYPEAVDFYDYYKGQMEPWDGPALVLFSDGK   450
 451  TVGACLDRNGLRPARYWRTSDNVVYVASEVGVLPMDESKVTMKGRLGPGM   500
 501  MISVDLENGQVYENTEVKKRVASYNPYGKWVSENLRNLKPSNYLSSAILE   550
 551  TDETLRRQQAFGYSSEDVQMVIESMAAQGKEPTFCMGDDTPVAVLSQKPH   600
 601  MLYDYFKQRFAQVTNPAIDPLREGLVMSLEVNIGKRGNILEVGPQNVSQV   650
 651  VLSGPVLNERELEGLLGDPLLKSQILPTFFDIRRGIEGSLKKGLLKLCEA   700
 701  ADEAVRNGSQVLVLSDRSDNPEPTRPAIPMLLAVGAVHQHLIQNGLRMSA   750
 751  SIIADTAQCFSTHHFACLIGYGASAICPHLALETCRQWRLSNKTVNMMRN   800
 801  GKMPTVTMEQAQKNYRKAVNTGLLKVLSKMGISLFSSYCGAQIFEIYGLG   850
 851  NEVVEFSFRGSASQIGGLTLDELARETLTFWVRAFSEDTAKRLENFGFIQ   900
 901  FRPGGEYHGNNPEMSKLLHKAVREKSETAYAVYQQHLANRPITVFRDLLE   950
 951  FKSDRNPIPVGKVEPASSIVERFCTGGMSLGAISRETHETIAIAMNRLGG  1000
1001  KSNSGEGGEDPIRWKPLTDVVDGYSSTLPHLKGLRNGDTATSAIKQVASG  1050
1051  RFGVTPTFLVNADQLEIKVAQGAKPGEGGQLPGKKVSAYIARLRNSKPGV  1100
1101  PLISPPPHHDIYSIEDLAQLIFDLHQVNPKAKVSVKLVSETGIGTVASGV  1150
1151  AKANADIIQISGYDGGTGASPISSIKHAGGPWELGLAETQKTLIGNGLRE  1200
1201  RVIIRVDGGFKSGVDVLIAAAMGADEYGFGTLAMIATGCIMARICHTNNC  1250
1251  PVGVASQREELRARFPGLPGDLVNFFLYIAEEVRGILAQLGYEKLDDIIG  1300
1301  RTDLLKARDISLVKTHLDLSYLLSSVGLPKRSSTSIRKQEVHSNGPVLDD  1350
1351  TLLQDPEIMDAIENEKTVHKTMSIYNVDRSVCGRIAGVIAKKYGDTGFAG  1400
1401  QLNLTFTGSAGQSFACFLTPGMNIRLVGEANDYVGKGMAGGEVVILPVES  1450
1451  TGFRPEDATIVGNTCLYGATGGLLFVRGKAGERFAVRNSLAQAVVEGTGD  1500
1501  HCCEYMTGGCVVILGKVGRNVAAGMTGGLAYILDEDNTLLPKMNKEIVKI  1550
1551  QRVTSPVGQTQLKSLIQAHVEKTGSSKGAMIVEEWDKYLAMFWQLVPPSE  1600
1601  EDTPEANSDHILKTTTGDEEQVSSTLAEK                       1629

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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