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

NucPred

Fetching Q62901 from www.uniprot.org...

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

   1  MTADKDKDKDKEKDRDRDRDRERDKRDKARESENARPRRSCTLEGGAKNY    50
  51  AESDHSEDEDNDNGATTEESARKSRKKPPKKKSRYERTDTGEITSYITED   100
 101  DVVYRPGDCVYIESRRPNTPYFICSIQDFKLVHNSQACCRSPAPALCDPP   150
 151  ACSLPVASQPPQHLSEAGRGPVGSKRDHLLMNVKWYYRQSEVPDSVYQHL   200
 201  VQDRHNENDSGRELVITDPVIKNRELFISDYVDTYHAAALRGKCNISHFS   250
 251  DIFAAREFKARVDSFFYILGYNPETRRLNSTQGEIRVGPSHQAKLPDLQP   300
 301  FPSPDGDTVTQHEELVWMPGVSDCDLLMYLRAARSMAAFAGMCDGGSTED   350
 351  GCVAASRDDTTLNALNTLHESSYDAGKALQRLVKKPVPKLIEKCWTEDEV   400
 401  KRFVKGLRQYGKNFFRIRKELLPNKETGELITFYYYWKKTPEAASSRAHR   450
 451  RHRRQAVFRRIKTRTASTPVNTPSRPPSSEFLDLSSASEDDFDSEDSEQE   500
 501  LKGYACRHCFTTTSKDWHHGGRENILLCTDCRIHFKKYGELPPIEKPVDP   550
 551  PPFMFKPVKEEDDGLSGKHSMRTRRSRGSMSTLRSGRKKQPASPDGRASP   600
 601  VNEDVRSSGRNSPSAASTSSNDSKAEAVKKSAKKVKEEAASPLKNTKRQR   650
 651  EKVASDTEDTDRATSKKTKTQEISRPNSPSEGEGESSDSRSVNDEGSSDP   700
 701  KDIDQDNRSTSPSIPSPQDNESDSDSSAQQQMLQTQPPALQAPSGAASAP   750
 751  STAPPGTTQLPTPGPTPSATTVPPQGSPATSQPPNQTQSTVAPAAHTLIQ   800
 801  QTPTLHPPRLPSPHPPLQPMTAPPSQNSAQPHPQPSLHGQGPPGPHSLQT   850
 851  GPLLQHPGPPQPFGLTPQSSQGQGPLGPSPAAAHPHSTIQLPASQSALQP   900
 901  QQPPREQPLPPAPLAMPHIKPPPTTPIPQLPAPQAHKHPPHLSGPSPFSM   950
 951  NANLPPPPALKPLSSLSTHHPPSAHPPPLQLMPQSQPLPSSPAQPPGLTQ  1000
1001  SQSLPPPAASHPTTGGLHQVPSQSPFPQHPFVPGGPPPITPPSCPPTSTP  1050
1051  PAGPSSSSQPPCSAAVSSGGNVPGAPSCPLPAVQIKEEALDEAEEPESPP  1100
1101  PPPRSPSPEPTVVDTPSHASQSARFYKHLDRGYNSCARTDLYFMPLAGSK  1150
1151  LAKKREEAIEKAKREAEQKAREEREREKEKEKEREREREREREAERAAQK  1200
1201  ASSSAHEGRLSDPQLSGPGHMRPSFEPPPTTIAAVPPYIGPDTPALRTLS  1250
1251  EYARPHVMSPTNRNHPFYMPLNPTDPLLAYHMPGLYNVDPTIRERELRER  1300
1301  EIREREIRERELRERMKPGFEVKPPELDPLHPATNPMEHFARHSALTIPP  1350
1351  AAGPHPFASFHPGLNPLERERLALAGPQLRPEMSYPDRLAAERIHAERMA  1400
1401  SLTSDPLARLQMFNVTPHHHQHSHIHSHLHLHQQDPLHQGSAGPVHPLVD  1450
1451  PLTAGPHLARFPYPPGTLPNPLLGQPPHEHEMLRHPVFGTPYPRDLPGAI  1500
1501  PPPMSAAHQLQAMHAQSAELQRLAMEQQWLHGHPHMHGGHLPSQEDYYSR  1550
1551  LKKEGDKQL                                           1559

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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