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

NucPred

Fetching O97758 from www.uniprot.org...

The NucPred score for your sequence is 0.92 (see score help below)

   1  MSARAAAAKNTAMEETAIWEQHTVTLHRAPGFGFGIAISGGRDNPHFQSG    50
51 ETSIVISDVLKGGPAEGQLQENDRVAMVNGVSMDNVEHAFAVQQLRKSGK 100
101 NAKITIRRKKKVQIPVSRPDPEPVSENEDSYDEEVHDPRSSRGGLVSRRS 150
151 EKSWARDRSASRERSLSPRSDRRSVASSQPPKPTKVTLVKSRKNEEYGLR 200
201 LASHIFVKEISQDSLAARDGNIQEGDVVLKINGTVTENMSLTDAKTLIER 250
251 SKGKLKMVVQRDERATLLNVPDLSDSIHSANASERDDISEIQSLASDHSG 300
301 RSHDRPPRHSRSRSPDQRSEPSDHSRHSPQQPSSGSLRSREEERISKPGA 350
351 VSTPVKHADDHTHKTVEEVVVERNEKQAPSLPEPKPVYAQVGQPDVDLPV 400
401 SPSDGVLPNSTHEDGILRPSMKLVKFRKGDSVGLRLAGGNDVGIFVAGVL 450
451 EDSPAAKEGLEEGDQILRVNNVDFTNIIREEAVLFLLDLPKGEEVTILAQ 500
501 KKKDVYRRIVESDVGDSFYIRTHFEYEKESPYGLSFNKGEVFRVVDTLYN 550
551 GKLGSWLAIRIGKNHKEVERGIIPNKNRAEQLASVQYTLPKTAGGDRADF 600
601 WRFRGLRSSKRNLRKSREDLSAQPVQTKFPAYERVVLREAGFLRPVTIFG 650
651 PIADVAREKLAREEPDIYQIAKSEPRDAGTDQRSSGIIRLHTIKQIIDQD 700
701 KHALLDVTPNAVDRLNYAQWYPIVVFLNPDSKQGVKTMRMRLCPESRKSA 750
751 RKLYERSHKLRKNNHHLFTTTINLNSMNDGWYGALKEAIQQQQNQLVWVS 800
801 EGKADGATSDDLDLHDDRLSYLSAPGSEYSMYSTDSRHTSDYEDTDTEGG 850
851 AYTDQELDETLNDEVGTPPESAITRSSEPVREDSSGMHHENQTYPPYSPQ 900
901 AQPQPIHRIDSPGFKTASQQKAEASSPVPYLSPETNPASSTSAVNHNVTL 950
951 TNVRLEGPTPAPSTSYSPQADSLRTPSTEAAHIMLRDQEPSLPSHVEPAK 1000
1001 VYRKDPYPEEMMRQNHVLKQPAVGHPGQRPDKEPNLSYESQPPYVEKQAN 1050
1051 RDLEQPTYRYDSSSYTDQFSRNYDHRLRYEERIPTYEEQWSYYDDKQPYQ 1100
1101 PRPSLDNQHPRDLDSRQHPEESSERGSYPRFEEPAPLSYDSRPRYDQPPR 1150
1151 TSTLRHEEQPTPGYDMHNRYRPEAQSYSSAGPKASEPKQYFDQYPRSYEQ 1200
1201 VPSQGFSSKAGHYEPLHGAAVVPPLIPASQHKPEVLPSNTKPLPPPPTLT 1250
1251 EEEEDPAMKPQSVLTRVKMFENKRSASLENKKDENHTAGFKPPEVASKPP 1300
1301 GAPIIGPKPTPQNQFSEHDKTLYRIPEPQKPQMKPPEDIVRSNHYDPEED 1350
1351 EEYYRKQLSYFDRRSFENKPSTHIPAGHLSEPAKPVHSQNQTNFSSYSSK 1400
1401 GKSPEADAPDRSFGEKRYEPVQATPPPPPLPSQYAQPSQPGTSSSLALHT 1450
1451 HAKGAHGEGNSISLDFQNSLVSKPDPPPSQNKPATFRPPNREDTVQSTFY 1500
1501 PQKSFPDKAPVNGAEQTQKTVTPAYNRFTPKPYTSSARPFERKFESPKFN 1550
1551 HNLLPSETAHKPDLSSKAPASPKTLAKAHSRAQPPEFDSGVETFSIHADK 1600
1601 PKYQMNNLSTVPKAIPVSPSAVEEDEDEDGHTVVATARGVFNNNGGVLSS 1650
1651 IETGVSIIIPQGAIPEGVEQEIYFKVCRDNSILPPLDKEKGETLLSPLVM 1700
1701 CGPHGLKFLKPVELRLPHCASMTPDGWSFALKSSDSSSGDPKTWQNKCLP 1750
1751 GDPNYLVGANCVSVLIDHF 1769

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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