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

NucPred

Fetching Q9H2M9 from www.uniprot.org...

The NucPred score for your sequence is 0.39 (see score help below)

   1  MACSIVQFCYFQDLQAARDFLFPHLREEILSGALRRDPSKSTDWEDDGWG    50
  51  AWEENEPQEPEEEGNTCKTQKTSWLQDCVLSLSPTNDLMVIAREQKAVFL   100
 101  VPKWKYSDKGKEEMQFAVGWSGSLNVEEGECVTSALCIPLASQKRSSTGR   150
 151  PDWTCIVVGFTSGYVRFYTENGVLLLAQLLNEDPVLQLKCRTYEIPRHPG   200
 201  VTEQNEELSILYPAAIVTIDGFSLFQSLRACRNQVAKAAASGNENIQPPP   250
 251  LAYKKWGLQDIDTIIDHASVGIMTLSPFDQMKTASNIGGFNAAIKNSPPA   300
 301  MSQYITVGSNPFTGFFYALEGSTQPLLSHVALAVASKLTSALFNAASGWL   350
 351  GWKSKHEEEAVQKQKPKVEPATPLAVRFGLPDSRRHGESICLSPCNTLAA   400
 401  VTDDFGRVILLDVARGIAIRMWKGYRDAQIGWIQTVEDLHERVPEKADFS   450
 451  PFGNSQGPSRVAQFLVIYAPRRGILEVWSTQQGPRVGAFNVGKHCRLLYP   500
 501  GYKIMGLNNVTSQSWQPQTYQICLVDPVSGSVKTVNVPFHLALSDKKSER   550
 551  AKDMHLVKKLAALLKTKSPNLDLVETEIKELILDIKYPATKKQALESILA   600
 601  SERLPFSCLRNITQTLMDTLKSQELESVDEGLLQFCANKLKLLQLYESVS   650
 651  QLNSLDFHLDTPFSDNDLALLLRLDEKELLKLQALLEKYKQENTRTNVRF   700
 701  SDDKDGVLPVKTFLEYLEYEKDVLNIKKISEEEYVALGSFFFWKCLHGES   750
 751  STEDMCHTLESAGLSPQLLLSLLLSVWLSKEKDILDKPQSICCLHTMLSL   800
 801  LSKMKVAIDETWDSQSVSPWWQQMRTACIQSENNGAALLSAHVGHSVAAQ   850
 851  ISNNMTEKKFSQTVLGADSEALTDSWEALSLDTEYWKLLLKQLEDCLILQ   900
 901  TLLHSKGNTQTSKVSSLQAEPLPRLSVKKLLEGGKGGIADSVAKWIFKQD   950
 951  FSPEVLKLANEERDAENPDEPKEGVNRSFLEVSEMEMDLGAIPDLLHLAY  1000
1001  EQFPCSLELDVLHAHCCWEYVVQWNKDPEEARFFVRSIEHLKQIFNAHVQ  1050
1051  NGIALMMWNTFLVKRFSAATYLMDKVGKSPKDRLCRRDVGMSDTAMTSFL  1100
1101  GSCLDLLQILMEADVSRDEIQVPVLDTEDAWLSVEGPISIVELALEQKHI  1150
1151  HYPLVEHHSILCSILYAVMRFSLKTVKPLSLFDSKGKNAFFKDLTSIQLL  1200
1201  PSGEMDPNFISVRQQFLLKVVSAAVQAQHSATKVKDPTEEATPTPFGKDQ  1250
1251  DWPALAVDLAHHLQVSEDVVRRHYVGELYNYGVDHLGEEAILQVHDKEVL  1300
1301  ASQLLVLTGQRLAHALLHTQTKEGMELLARLPPTLCTWLKAMDPQDLQNT  1350
1351  EVPIATTAKLVNKVIELLPEKHGQYGLALHLIEAVEAISLPSL         1393

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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