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

NucPred

Fetching P05690 from www.uniprot.org...

The NucPred score for your sequence is 0.76 (see score help below)

   1  MRSIIIASLVALALASSPAFERTFEPKTDYHYKFDGLVLSGLPSASSELS    50
  51  QSRISARARIQAVDDRYIHLQLVNIRMAASHLPESEQMPSLNSMEQRELS   100
 101  EEYKQMLELPLRAQLRNGLISELQFDKEDAEWSKNMKRAVVNMISFNPIA   150
 151  PRNEIEKIESSYDKEEQSEENTSFFTNEKTLEGDCQVAYTVIREQKKTII   200
 201  TKSINFDKCTERSEIAYGLRYSSECPECEKDTELIRPQTVYTYVLENEEL   250
 251  KESEVRSLYTVNVNGQEVMKTETRSKLVLEENHSIKSHIKKVNGEKESII   300
 301  YSSRWEQLVEDFFKNGDKAEFAPFEKFPLDKKMHLIKTITEQIQEVENNM   350
 351  PETSHFLARLVRIFRTTSTSQLKEIHETLYVKADKKIQSLMEHALAIAGT   400
 401  KNTIQHILVHMENEDILPLGQILKTIQETPFPSQSIAEALIKFAESRVAK   450
 451  NNLVVRQAAWLAAGSVVRGIVDYKNIRPLVREDKRELKEKFLRVFMQQYK   500
 501  DAETTYEKILALKTIGNAGLDISVNQLNEIIVDKRQPLPVRKEAIDALRL   550
 551  LKDTMPRKIQKVLLPIYKNRQYEPEIRMLALWRMMHTRPEESLLVQVVSQ   600
 601  MEKETNQQVAALTHQMIRHFAMSTNPCYQRVAIVCSKVLSFTRYQPQEQM   650
 651  IASSYAQLPLFLQNSFSGAQFDFAAIFEKNSFLPKDLHASLDAVFGGNWN   700
 701  KYFAQIGFSQQHMDKYVQMALEKLESLEKESTTVVRGRRIQTGIKLLKEL   750
 751  AQKMNIRARPATYTEKDAFAMVYLRYKDMDYAFLPIDRQLVENLIEKFTS   800
 801  NGKVQFSEIRRLLNQELEFETHHAAYFYEAIRKFPTTLGLPLTISGKIPT   850
 851  VISAEGQFSLELEGTELRLTVEARPSVAATHVYEMRMFTPLFEQGVKSVQ   900
 901  SVRAYTPIKIQAVAGMKRNFEIVYKVVVPENQKSIVSLTTRPVVFLRFPG   950
 951  FSKFEYIEAEERTVVVPQWQQKTQEIEKVFNFLGLEVSTRGNILNQHTLE  1000
1001  NWLLAEQDFEVSVENKNRPAEFTARLTVGQLEKTELSQIKYNKIFEKEFE  1050
1051  LEQENTESRREYFNKMVKNIQKEQGYKSVISLKLEAPRDYTMNTELTTVC  1100
1101  DKQVRMCQWEVEIRRSPILEETKEWTLRSQLLVVRPEMPSSLRQLRDQPH  1150
1151  REVQLSLTSTWGSQKKSEVTVNAQLQQSKEQKKYERNMDRQFNGMPEYEL  1200
1201  LIKAARLNQINAVAEYKLTRETEQVLARYFDLVKTYNYWTVSSRPENNEN  1250
1251  DRVVVQLTVEPMSRQYVNITMQSPMERIELKNVQVPRVYLPSIAQRSVKH  1300
1301  QLTEASGSVCKVQKNQIRTFDDVLYNTPLTTCYSLIAKDCSEEPTFAVLS  1350
1351  KKTEKNSEEMIIKVIRGEQEIVAQLQNEEIRVKVDGKKIQSEDYSAYQIE  1400
1401  RLGESAIVIELPEGEVRFDGYTIKTQLPSYSRKNQLCGLCGNNDDESTNE  1450
1451  FYTSDNTETEDIEEFHRSYLLKNEECEAEEERLSEKKNYRKYERDEEQSD  1500
1501  EYSSEETYDYEQENTKKSQKNQRSQKKSDLVEKTQIKEFSHRICFSVEPV  1550
1551  AECRRGYEVEQQQQRKIRFTCLQRHNRDASRLLKESRQQPLQLDDYPVSF  1600
1601  VESVKVPTACVAY                                       1613

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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