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

NucPred

Fetching Q80Z38 from www.uniprot.org...

The NucPred score for your sequence is 0.93 (see score help below)

   1  MKSLLNAFTKKEVPFREAPAYSNRRRRPPNTLAAPRVLLRSNSDNNLNAG    50
  51  APEWAVCSAATSHRSLSPQLLQQTPSKPDGATKSLGSYTPGPRSRSPSLN   100
 101  RLGGTAEDGKRTQPHWHVGSPFTPGANKDSLSTFEYPGPRRKLYSAVPGR   150
 151  LFVAVKPYQPQVDGEIPLHRGDRVKVLSIGEGGFWEGSARGHIGWFPAEC   200
 201  VEEVQCKPRDSQAETRADRSKKLFRHYTVGSYDSFDAASDCIIEDKTVVL   250
 251  QKKDNEGFGFVLRGAKADTPIEEFTPTPAFPALQYLESVDEGGVAWQAGL   300
 301  RTGDFLIEVNNENVVKVGHRQVVNMIRQGGNHLILKVVTVTRNLDPDDTA   350
 351  RKKAPPPPKRAPTTALTLRSKSMTAELEELGLSLVDKASVRKKKDKPEEI   400
 401  VPASKPSRTAENVAIESRVATIKQRPTSRCFPAASDVNSVYERQGIAVMT   450
 451  PTVPGSPKGPFLGLPRGTMRRQKSIDSRIFLSGITEEERQFLAPPMLKFT   500
 501  RSLSMPDTSEDIPPPPQSVPPSPPPPSPTTYNCPRSPTPRVYGTIKPAFN   550
 551  QNPVVAKVPPATRSDTVATMMREKGMFYRRELDRFSLDSEDVYSRSPAPQ   600
 601  AAFRTKRGQMPENPYSEVGKIASKAVYVPAKPARRKGVLVKQSNVEDSPE   650
 651  KTCSIPIPTIIVKEPSTSSSGKSSQGSSMEIDPQATEPGQLRPDDSLTVS   700
 701  SPFAAAIAGAVRDREKRLEARRNSPAFLSTDLGDEDVGLGPPAPRMQASK   750
 751  FPEEGGFGDEDETEQPLLPTPGAAPRELENHFLGGGEAGAQGEAGGPLSS   800
 801  TSKAKGPESGPAAPLKSSSPAGPENYVHPLTGRLLDPSSPLALALSARDR   850
 851  AMQESQQGHKGEAPKADLNKPLYIDTKMRPSVESGFPPVTRQNTRGPLRR   900
 901  QETENKYETDLGKDRRADDKKNMLINIVDTAQQKSAGLLMVHTVDVPMAG   950
 951  PPLEEEEDREDGDTKPDHSPSTVPEGVPKTEGALQISAAPEPAVAPGRTI  1000
1001  VAAGSVEEAVILPFRIPPPPLASVDLDEDFLFTEPLPPPLEFANSFDIPD  1050
1051  DRAASVPALADLVKQKKNDTSQPPTLNSSQPANSTDSKKPAGISNCLPSS  1100
1101  FLPPPESFDAVTDSGIEEVDSRSSSDHHLETTSTISTVSSISTLSSEGGE  1150
1151  SMDTCTVYADGQAFVVDKPPVPPKPKMKPIVHKSNALYQDTLPEEDTDGF  1200
1201  VIPPPAPPPPPGSAQAGVAKVIQPRTSKLWGDVPEVKSPILSGPKANVIS  1250
1251  ELNSILQQMNRGKSVKPGEGLELPVGAKSANLAPRSPEVMSTVSGTRSTT  1300
1301  VTFTVRPGTSQPITLQSRPPDYESRTSGPRRAPSPVVSPTELSKEILPTP  1350
1351  PPPSATAASPSPTLSDVFSLPSQSPAGDLFGLNPAGRSRSPSPSILQQPI  1400
1401  SNKPFTTKPVHLWTKPDVADWLESLNLGEHKETFMDNEIDGSHLPNLQKE  1450
1451  DLIDLGVTRVGHRMNIERALKQLLDR                          1476

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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