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

NucPred

Fetching P55155 from www.uniprot.org...

The NucPred score for your sequence is 0.73 (see score help below)

   1  MRSIIIASIVALAIAFSPAFERTFEPKIDYHYKFDGLVLSGLPTASSELS    50
  51  QSRFSARVRIQAVDDRHIHLQLVNIHMAASHLPESEQIPSLNSMEQRELS   100
 101  EEYKQMLKLPLRAQLRNGLIAELQFDKEDAEWSKNMKRAVVNMISFNPIA   150
 151  PRNEIEKIESSYDKEEQSEENTSFFTNEKTLEGDCQVAYTVIREQKKTII   200
 201  TKSINFDKCTERSEIAYGLRYSSECPECEKDTVLIRPQTVYTYILENEEL   250
 251  KESEVRSLYTVNVNGQEVMKTETRSKLVLEENHSIKSHIEKVNGEKESII   300
 301  YSSRWEQLVEDFFKNGDKAEFAPFEKFPLDKKMHLIKTITEQIQEVENNI   350
 351  PETSHFLARLVRIFRTTSTSQLKEIHETLYVKADKKIQSLMEHALAIAGT   400
 401  KNTIQHILVHIENEDIVPLEAAQLLKSIQETPFPSQTIAEALIKFAESRV   450
 451  SKNNQVVRQSAWLAAGSVVRGIVDYKNIRPLVREDKRELKEKFLRVFMQQ   500
 501  YKDAETTYEKILALKSIGNAGLDISVNQLNEIIVDKRQLLPVRKEAIDAL   550
 551  RLLKDTMPRKIQKVLLPIYKNRQYEPEIRMLALWRMMHTRPEESLLVQVV   600
 601  SQMEKETNQQVAALTHQMIRHFAKSTNPCYQRVAIVCSKVLSFTRYQPQE   650
 651  QMIASSYAQLPLFLQNSFSGAQFDFAAIFEKNSFLLKDLHASLDAVFGGN   700
 701  WNKYFAQIGFSQQHMDKYVQMALEKLESIEKESTTVVRGRRIQTGITLLK   750
 751  ELALKMNIRARPANYNEKDAFAMVYLRYKDMDYAILPVDTQLIEKLIEKY   800
 801  ISNGKVQFSEIRRLLNQEHEFETHHAAYFYEAIRKFPTTLGLPLIVSGKI   850
 851  PTVFSAEGQFSLGLEETELRLTVEARPSVAATHVYEMRMFTPLFEQGVKS   900
 901  VQSVRAYTPIKIQAVVGMKRNFEIVYKVVVPENQKSIISLTTRPVVFLRF   950
 951  PGFSKFEYIEAEERTVVVPQWQQKTQEIEKVFNFLGLEVSTRGNILNQHT  1000
1001  LENWLLAEQDFEVSVENKYRPAEFTARLTVGQLEKTELSQIKYNKIFEKE  1050
1051  FELEQENTESRREYFTKMVKSIQKEQGYKSVVSLRLEAPRDYTMNTEVTT  1100
1101  VCDKQVRMCQWEVEIRRSPILEETKEWTLRSQLLVVRPEMPSSLRQLHDQ  1150
1151  PHREVQLSLTSTWGSQKKSEVTVNAQLQQSKEQKKYERNMDRHFNGMPEY  1200
1201  ELLIKAARLNQINAVAEYKLTRETEQVLARYFDLVKAYNYWTVSSRPENN  1250
1251  ENDRVVVQLTVEPMSRQYVNITMQSPIERVELKNVQVPRVYLPSIAQRSV  1300
1301  KHLLNEASGSVCKVQKNQIRTFDDVLYNTPLTTCYSLIAKDCSEEPTFAV  1350
1351  LSKKTEKNSEEMIIKVIRGEQEIVAQLQNEEIRVKVDGKKILSEDYSAHQ  1400
1401  IERLGESDIVIELPEGEVRFDGYTIKTQLPSYSRKNQLCGLCGNNDDEST  1450
1451  NEFYTSDNTETKDIEEFHRSYLLKNEECEAEEERLSEKKNYRKYDERKYE  1500
1501  SEEYSFEETYDYEQENTNKKQKNQRSQKKSDLVEKTQIKEFSHRICFSVE  1550
1551  PVAECRRRGYEAVEQQQRKVRFTCLPRHSSEARRLVKEARQGTVQLDDHK  1600
1601  ISFVHSVQVPVACVAY                                    1616

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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