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

NucPred

Fetching Q9UMZ2 from www.uniprot.org...

The NucPred score for your sequence is 0.84 (see score help below)

   1  MALRPGAGSGGGGAAGAGAGSAGGGGFMFPVAGGIRPPQAGLMPMQQQGF    50
  51  PMVSVMQPNMQGIMGMNYSSQMSQGPIAMQAGIPMGPMPAAGMPYLGQAP   100
 101  FLGMRPPGPQYTPDMQKQFAEEQQKRFEQQQKLLEEERKRRQFEEQKQKL   150
 151  RLLSSVKPKTGEKSRDDALEAIKGNLDGFSRDAKMHPTPASHPKKPGPSL   200
 201  EEKFLVSCDISTSGQEQIKLNTSEVGHKALGPGSSKKYPSLMASNGVAVD   250
 251  GCVSGTTTAEAENTSDQNLSIEESGVGVFPSQDPAQPRMPPWIYNESLVP   300
 301  DAYKKILETTMTPTGIDTAKLYPILMSSGLPRETLGQIWALANRTTPGKL   350
 351  TKEELYTVLAMIAVTQRGVPAMSPDALNQFPAAPIPTLSGFSMTLPTPVS   400
 401  QPTVIPSGPAGSMPLSLGQPVMGINLVGPVGGAAAQASSGFIPTYPANQV   450
 451  VKPEEDDFQDFQDASKSGSLDDSFSDFQELPASSKTSNSQHGNSAPSLLM   500
 501  PLPGTKALPSMDKYAVFKGIAADKSSENTVPPGDPGDKYSAFRELEQTAE   550
 551  NKPLGESFAEFRSAGTDDGFTDFKTADSVSPLEPPTKDKTFPPSFPSGTI   600
 601  QQKQQTQVKNPLNLADLDMFSSVNCSSEKPLSFSAVFSTSKSVSTPQSTG   650
 651  SAATMTALAATKTSSLADDFGEFSLFGEYSGLAPVGEQDDFADFMAFSNS   700
 701  SISSEQKPDDKYDALKEEASPVPLTSNVGSTVKGGQNSTAASTKYDVFRQ   750
 751  LSLEGSGLGVEDLKDNTPSGKSDDDFADFHSSKFSSINSDKSLGEKAVAF   800
 801  RHTKEDSASVKSLDLPSIGGSSVGKEDSEDALSVQFDMKLADVGGDLKHV   850
 851  MSDSSLDLPTVSGQHPPAADIEDLKYAAFGSYSSNFAVSTLTSYDWSDRD   900
 901  DATQGRKLSPFVLSAGSGSPSATSILQKKETSFGSSENITMTSLSKVTTF   950
 951  VSEDALPETTFPALASFKDTIPQTSEQKEYENRDYKDFTKQDLPTAERSQ  1000
1001  EATCPSPASSGASQETPNECSDDFGEFQSEKPKISKFDFLVATSQSKMKS  1050
1051  SEEMIKSELATFDLSVQGSHKRSLSLGDKEISRSSPSPALEQPFRDRSNT  1100
1101  LNEKPALPVIRDKYKDLTGEVEENERYAYEWQRCLGSALNVIKKANDTLN  1150
1151  GISSSSVCTEVIQSAQGMEYLLGVVEVYRVTKRVELGIKATAVCSEKLQQ  1200
1201  LLKDIDKVWNNLIGFMSLATLTPDENSLDFSSCMLRPGIKNAQELACGVC  1250
1251  LLNVDSRSRKEEKPAEEHPKKAFNSETDSFKLAYGGHQYHASCANFWINC  1300
1301  VEPKPPGLVLPDLL                                      1314

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.)

Go back to the NucPred Home Page.