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

NucPred

Fetching P46974 from www.uniprot.org...

The NucPred score for your sequence is 0.96 (see score help below)

   1  MEPFAFGRGAPALCILTAAARINLDNFVPCCWALFRLSFFFPLDPAYIRN    50
  51  ENKETRTSWISIEFFFFVKHCLSQHTFFSKTLAPKRNFRAKKLKDIGDTR   100
 101  IDRADKDFLLVPEPSMFVNGNQSNFAKPAGQGILPIPKKSRIIKTDKPRP   150
 151  FLCPTCTRGFVRQEHLKRHQHSHTREKPYLCIFCGRCFARRDLVLRHQQK   200
 201  LHAALVGTGDPRRMTPAPNSTSSFASKRRHSVAADDPTDLHIIKIAGNKE   250
 251  TILPTPKNLAGKTSEELKEAVVALAKSNNVELPVSAPVMNDKREKTPPSK   300
 301  AGSLGFREFKFSTKGVPVHSASSDAVIDRANTPSSMHKTKRHASFSASSA   350
 351  MTYMSSSNSPHHSITNFELVEDAPHQVGFSTPQMTAKQLMESVSELDLPP   400
 401  LTLDEPPQAIKFNLNLFNNDPSGQQQQQQQQQQNSTSSTIVNSNNGSTVA   450
 451  TPGVYLLSSGPSLTDLLTMNSAHAGAGGYMSSHHSPFDLGCFSHDKPTVS   500
 501  EFNLPSSFPNTIPSNSTTASNSYSNLANQTYRQMSNEQPLMSLSPKNPPT   550
 551  TVSDSSSTINFNPGTNNLLEPSMEPNDKDSNIDPAAIDDKWLSEFINNSD   600
 601  PKSTFKINFNHFNDIGFIYSPPSSRSSIPNKSPPNHSATSLNHEKASLSP   650
 651  RLNLSLNGSTDLPSTPQNQLKEPSYSDPISHSSHKRRRDSVMMDYDLSNF   700
 701  FSSRQLDISKVLNGTEQNNSHVNDDVLTLSFPGETDSNATQKQLPVLTPS   750
 751  DLLSPFSVPSVSQVLFTNELRSMMLADNNIDSGAFPTTSQLNDYVTYYKE   800
 801  EFHPFFSFIHLPSIIPNMDSYPLLLSISMVGALYGFHSTHAKVLANAAST   850
 851  QIRKSLKVSEKNPETTELWVIQTLVLLTFYCIFNKNTAVIKGMHGQLTTI   900
 901  IRLLKASRLNLPLESLCQPPIESDHIMEYENSPHMFSKIREQYNAPNQMN   950
 951  KNYQYFVLAQSRIRTCHAVLLISNLFSSLVGADCCFHSVDLKCGVPCYKE  1000
1001  ELYQCRNSDEWSDLLCQYKITLDSKFSLIELSNGNEAYENCLRFLSTGDS  1050
1051  FFYGNARVSLSTCLSLLISIHEKILIERNNARISNNNTNSNNIELDDIEW  1100
1101  KMTSRQRIDTMLKYWENLYLKNGGILTPTENSMSTINANPAMRLIIPVYL  1150
1151  FAKMRRCLDLAHVIEKIWLKDWSNMNKALEEVCYDMGSLREATEYALNMV  1200
1201  DAWTSFFTYIKQGKRRIFNTPVFATTCMFTAVLVISEYMKCVEDWARGYN  1250
1251  ANNPNSALLDFSDRVLWLKAERILRRLQMNLIPKECDVLKSYTDFLRWQD  1300
1301  KDALDLSALNEEQAQRAMDPNTDINETIQLIVAASLSSKCLYLGVQILGD  1350
1351  APIWPIILSFAHGLQSRAIYSVTKKRNTRI                      1380

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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