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

NucPred

Fetching Q80TZ9 from www.uniprot.org...

The NucPred score for your sequence is 0.97 (see score help below)

   1  MTADKDKDKDKEKDRDRDRDRERDKRDKARESENARPRRSCTLEGGAKNY    50
  51  AESDHSEDEDNDNNSATTEESNKKSRKKPPKKKSRYERTDTGEITSYITE   100
 101  DDVVYRPGDCVYIESRRPNTPYFICSIQDFKLVHSSQACCRSPAPAFCDP   150
 151  PACSLPVAPQPPQHLSEAGRGPGGSKRDHLLMNVKWYYRQSEVPDSVYQH   200
 201  LVQDRHNENDSGRELVITDPVIKNRELFISDYVDTYHAAALRGKCNISHF   250
 251  SDIFAAREFKARVDSFFYILGYNPETRRLNSTQGEIRVGPSHQAKLPDLQ   300
 301  PFPSPDGDTVTQHEELVWMPGVSDCDLLMYLRAARSMAAFAGMCDGGSTE   350
 351  DGCVAASRDDTTLNALNTLHESSYDAGKALQRLVKKPVPKLIEKCWTEDE   400
 401  VKRFVKGLRQYGKNFFRIRKELLPSKETGELITFYYYWKKTPEAASSRAH   450
 451  RRHRRQAVFRRIKTRTASTPVNTPSRPPSSEFLDLSSASEDDFDSEDSEQ   500
 501  ELKGYACRHCFTTTSKDWHHGGRENILLCTDCRIHFKKYGELPPIEKPVD   550
 551  PPPFMFKPVKEEDDGLSGKHSMRTRRSRGSMSTLRSGRKKQPTSPDGRAS   600
 601  PINEDIRSSGRNSPSAASTSSNDSKAETVKKSAKKVKEEAASPLKSTKRQ   650
 651  REKVASDTEDTDRITSKKTKTQEISRPNSPSEGEGESSDSRSVNDEGSSD   700
 701  PKDIDQDNRSTSPSIPSPQDNESDSDSSAQQQMLQAQPPALQAPSGAASA   750
 751  PSTAPPGTPQLPTQGPTPSATAVPPQGSPATSQPPNQTQSTVAPAAHTHI   800
 801  QQAPTLHPPRLPSPHPPLQPMTAPPSQSSAQPHPQPSLHSQGPPGPHSLQ   850
 851  TGPLLQHPGPPQPFGLPSQPSQGQGPLGPSPAAAHPHSTIQLPASQSALQ   900
 901  PQQPPREQPLPPAPLAMPHIKPPPTTPIPQLPAPQAHKHPPHLSGPSPFS   950
 951  LNANLPPPPALKPLSSLSTHHPPSAHPPPLQLMPQSQPLPSSPAQPPGLT  1000
1001  QSQSLPPPAASHPTTGLHQVPSQSPFPQHPFVPGGPPPITPPSCPPTSTP  1050
1051  PAGPSSSSQPPCSAAVSSGGSVPGAPSCPLPAVQIKEEALDEAEEPESPP  1100
1101  PPPRSPSPEPTVVDTPSHASQSARFYKHLDRGYNSCARTDLYFMPLAGSK  1150
1151  LAKKREEAIEKAKREAEQKAREEREREKEKEKEREREREREREAERAAKA  1200
1201  SSSAHEGRLSDPQLSGPGHMRPSFEPPPTTIAAVPPYIGPDTPALRTLSE  1250
1251  YARPHVMSPTNRNHPFYMPLNPTDPLLAYHMPGLYNVDPTIRERELRERE  1300
1301  IREREIRERELRERMKPGFEVKPPELDPLHPATNPMEHFARHSALTIPPA  1350
1351  AGPHPFASFHPGLNPLERERLALAGPQLRPEMSYPDRLAAERIHAERMAS  1400
1401  LTSDPLARLQMFNVTPHHHQHSHIHSHLHLHQQDPLHQGSAGPVHPLVDP  1450
1451  LTAGPHLARFPYPPGTLPNPLLGQPPHEHEMLRHPVFGTPYPRDLPGAIP  1500
1501  PPMSAAHQLQAMHAQSAELQRLAMEQQWLHGHPHMHGGHLPSQEDYYSRL  1550
1551  KKEGDKQL                                            1558

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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