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

NucPred

Fetching Q96K76 from www.uniprot.org...

The NucPred score for your sequence is 0.94 (see score help below)

   1  MVPGEENQLVPKEDVFWRCRQNIFDEMKKKFLQIENAAEEPRVLCIIQDT    50
  51  TNSKTVNERITLNLPASTPVRKLFEDVANKVGYINGTFDLVWGNGINTAD   100
 101  MAPLDHTSDKSLLDANFEPGKKNFLHLTDKDGEQPQILLEDSSAGEDSVH   150
 151  DRFIGPLPREGSGGSTSDYVSQSYSYSSILNKSETGYVGLVNQAMTCYLN   200
 201  SLLQTLFMTPEFRNALYKWEFEESEEDPVTSIPYQLQRLFVLLQTSKKRA   250
 251  IETTDVTRSFGWDSSEAWQQHDVQELCRVMFDALEQKWKQTEQADLINEL   300
 301  YQGKLKDYVRCLECGYEGWRIDTYLDIPLVIRPYGSSQAFASVEEALHAF   350
 351  IQPEILDGPNQYFCERCKKKCDARKGLRFLHFPYLLTLQLKRFDFDYTTM   400
 401  HRIKLNDRMTFPEELDMSTFIDVEDEKSPQTESCTDSGAENEGSCHSDQM   450
 451  SNDFSNDDGVDEGICLETNSGTEKISKSGLEKNSLIYELFSVMVHSGSAA   500
 501  GGHYYACIKSFSDEQWYSFNDQHVSRITQEDIKKTHGGSSGSRGYYSSAF   550
 551  ASSTNAYMLIYRLKDPARNAKFLEVDEYPEHIKNLVQKERELEEQEKRQR   600
 601  EIERNTCKIKLFCLHPTKQVMMENKLEVHKDKTLKEAVEMAYKMMDLEEV   650
 651  IPLDCCRLVKYDEFHDYLERSYEGEEDTPMGLLLGGVKSTYMFDLLLETR   700
 701  KPDQVFQSYKPGEVMVKVHVVDLKAESVAAPITVRAYLNQTVTEFKQLIS   750
 751  KAIHLPAETMRIVLERCYNDLRLLSVSSKTLKAEGFFRSNKVFVESSETL   800
 801  DYQMAFADSHLWKLLDRHANTIRLFVLLPEQSPVSYSKRTAYQKAGGDSG   850
 851  NVDDDCERVKGPVGSLKSVEAILEESTEKLKSLSLQQQQDGDNGDSSKST   900
 901  ETSDFENIESPLNERDSSASVDNRELEQHIQTSDPENFQSEERSDSDVNN   950
 951  DRSTSSVDSDILSSSHSSDTLCNADNAQIPLANGLDSHSITSSRRTKANE  1000
1001  GKKETWDTAEEDSGTDSEYDESGKSRGEMQYMYFKAEPYAADEGSGEGHK  1050
1051  WLMVHVDKRITLAAFKQHLEPFVGVLSSHFKVFRVYASNQEFESVRLNET  1100
1101  LSSFSDDNKITIRLGRALKKGEYRVKVYQLLVNEQEPCKFLLDAVFAKGM  1150
1151  TVRQSKEELIPQLREQCGLELSIDRFRLRKKTWKNPGTVFLDYHIYEEDI  1200
1201  NISSNWEVFLEVLDGVEKMKSMSQLAVLSRRWKPSEMKLDPFQEVVLESS  1250
1251  SVDELREKLSEISGIPLDDIEFAKGRGTFPCDISVLDIHQDLDWNPKVST  1300
1301  LNVWPLYICDDGAVIFYRDKTEELMELTDEQRNELMKKESSRLQKTGHRV  1350
1351  TYSPRKEKALKIYLDGAPNKDLTQD                           1375

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.)

Go back to the NucPred Home Page.