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

NucPred

Fetching O24367 from www.uniprot.org...

The NucPred score for your sequence is 0.35 (see score help below)

   1  MEIAGYRGGSLRGSLQGSLRRSVSAWRSPSTSDVFGRSSREEDDEEALKW    50
  51  AALEKLPTYDRLRKGIMTGDGGEIQEVDIQGLGFQERKNLLEKLVRNAEE   100
 101  DNERFLLKLRNRMERVGIDNPTIEVRFEHLNINAEAFVGNRGVPTLVNFF   150
 151  VNKAIWILSALHLMPSGKRPISILHDVSGIIKPCRMTLLLGPPGAGKTTL   200
 201  LLALAGKLDNTLKVTGNVTYNGHGMHEFVPQRTSAYISQHDVHIGEMTVR   250
 251  ETLAFSSRCQGVGTRYEMLTELSRREKEANIKPDPDVDVYMKAVAVEGQE   300
 301  SVVTDYILKILGLDICADTMVGDGMIRGISGGQKKRVTTGEMLVGPSKAL   350
 351  FMDEISTGLDSSTTFQIVNSLRQSVHILGGTALIALLQPAPETYDLFDDI   400
 401  LLLSDGQIVYQGPRENVLEFFESMGFKCPERKGVADFLQEVTSRKDQQQY   450
 451  WVRENEPYRFVPVNEFSEAFKSFHVGAKLHEELSTPFDRSRNHPAALTTS   500
 501  KYGISKMELLKACIDREWLLMKRNSFVYIFKVVQLIVLALIAMTVFFRTK   550
 551  LPRNGLEDATIFFGAMFLGLVTHLFNGFAELAMSIAKLPVFYKQRDLLFY   600
 601  PPWAYALPTWILKIPISFVECGVWIAMTYYVIGFDPNVVRMFRHYLLLVL   650
 651  ISQVASGLFRLLAAVGRDMVVADTFGAFAQLVLLVLGGFIIAREKIKKFW   700
 701  IWGYWSSPLMYAQNAIAVNEFLGHSWNKLVDATGQTLGERFLRNRGIFVD   750
 751  KNWYWIGVGALIGYMVLFNFLFILFLEWLDPLGKGQTTVSEEALQEKEAN   800
 801  RTGANVELATRGSAATSDGGSVEIRKDGNRKKGMVLPFTPLSITFDNVKY   850
 851  SVDMPQEMKDRGVTEDKLLLLKGVSGAFRPGVLTALMGVSGRGKTTLMDV   900
 901  LAGRKTGGYIEGDIRISGYPKNQETFARISGYCEQNDIHSPHVTVYESLL   950
 951  YSAWLRLPAEVDEKQRKMFVDEVMDLVELNSLRGSLVGLPGVTGLSTEQR  1000
1001  KRLTIAVELVANPSIIFMDEPTSGLDARAAAIVMRAVRNTVDTGRTVVCT  1050
1051  IHQPSIDIFEAFDELFLMKRGGEEIYVGPLGRQSSHLIKYFESIDGVKKI  1100
1101  KERYNPATWMLEVTTISQEEILGLNFAEVYRNSDLYKRNKDLIKELSTPP  1150
1151  PGSKDLFFATQFSQSFVMQCLACLWKQHKSYWRNPSYTATRLFFTVVIAL  1200
1201  IFGTIFWDLGKKRSTSLDLINAMGSMYAAVLFIGIQNAQTVQPIVDVERT  1250
1251  VFYREKAAGMYSALPYAYAQVLIEVPHILVQTLLYGLLVYSMIGFDWTAA  1300
1301  KFLWYMFFMFFTFLYFTYYGMMAVAMTPNSDIAAIVAAAFYAIWNIFAGF  1350
1351  IIPRPRIPIWWRWYYWACPVAWTLYGLVVSQFGEYTDTMSDVDETVKDFL  1400
1401  RRFLGFRHDFLPVVGVMVVVFTVLFASIFAFSIKTLNFQRR           1441

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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