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

NucPred

Fetching P49791 from www.uniprot.org...

The NucPred score for your sequence is 0.81 (see score help below)

   1  MASGAGGIGGGGGGGKIRTRRCHQGPVKPYQQGRPQHQGILSRVTESVKN    50
  51  IVPGWLQRYFNKSENACSCSVNADEVPRWPENREDEREIYVDENTNTDDG   100
 101  RTTPEPTGSNTEEPSTTSTASNYPDVLTRPSLHRSHLNFSVLESPALHCQ   150
 151  PSTSSAFPIGSSGFSLVKEIKDSTSQHDDDNISTTSGFSSRASEKDIAVS   200
 201  KNTSLPPLWSPEAERSHSLSQHTAISSKKPAFNLSAFGTLSTSLGNSSIL   250
 251  KTSQLGDSPFYPGKTTYGGAAAAVRQNKVRSTPYQAPVRRQMKAKQLNAQ   300
 301  SYGVTSSTARRILQSLEKMSSPLADAKRIPSAVSSPLNSPLDRSGIDSTV   350
 351  FQAKKEKVDSQYPPVQRLMTPKPVSIATNRTVYFKPSLTPSGDLRKTNQR   400
 401  IDKKNSTVDEKNISRQNREQESGFSYPNFSIPAANGLSSGVGGGGGKMRR   450
 451  ERTTHFVASKPSEEEEVEVPLLPQISLPISSSSLPTFNFSSPAISAASSS   500
 501  SVSPSQPLSNKVQMTSLGSTGNPVFTFSSPIVKSTQADVLPPASIGFTFS   550
 551  VPLAKTELSGPNSSSETVLSSSVTAQDNTVVNSSSSKKRSAPCEDPFTPA   600
 601  KILREGSVLDILKTPGFMSPKVDSPALQPTTTSSIVYTRPAISTFSSSGV   650
 651  EFGESLKAGSSWQCDTCLLQNKVTDNKCIACQAAKLPLKETAKQTGIGTP   700
 701  SKSDKPASTSGTGFGDKFKPAIGTWDCDTCLVQNKPEAVKCVACETPKPG   750
 751  TGVKRALPLTVASESPVTASSSTTVTTGTLGFGDKFKRPVGSWECPVCCV   800
 801  SNKAEDSRCVSCTSEKPGLVSASSSNSVPVSLPSGGCLGLDKFKKPEGSW   850
 851  DCEVCLVQNKADSTKCIACESAKPGTKSEFKGFGTSSSLNPAPSAFKFGI   900
 901  PSSSSGLSQTFTSTGNFKFGDQGGFKLGTSSDSGSTNTMNTNFKFPKPTG   950
 951  DFKFGVLPDSKPEEIKNDSKNDNFQFGPSSGLSNPASSAPFQFGVSTLGQ  1000
1001  QEKKEELPQSSSAGFSFGAGVANPSSAAIDTTVTSENKSGFNFGTIDTKS  1050
1051  VSVTPFTYKTTEAKKEDASATKGGFTFGKVDSAALSSPSMFVLGRTEEKQ  1100
1101  QEPVTSTSLVFGKKADNEEPKCQPVFSFGNSEQTKDESSSKPTFSFSVAK  1150
1151  PSVKESDQLAKATFAFGNQTNTTTDQGAAKPAFSFLNSSSSSSSTPATSS  1200
1201  SASIFGSSTSSSSPPVAAFVFGQASNPVSSSAFGNSAESSTSQPLLFPQD  1250
1251  GKPATTSSTASAAPPFVFGTGASSNSTVSSGFTFGATTTSSSSGSFFVFG  1300
1301  TGHSAPSASPAFGANQTPTFGQSQGASQPNPPSFGSISSSTALFSAGSQP  1350
1351  VPPPTFGTVSSSSQPPVFGQQPSQSAFGSGTANASSVFQFGSSTTNFNFT  1400
1401  NNNPSGVFTFGASPSTPAAAAQPSGSGGFSFSQSPASFTVGSNGKNMFSS  1450
1451  SGTSVSGRKIKTAVRRKK                                  1468

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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