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

NucPred

Fetching Q12267 from www.uniprot.org...

The NucPred score for your sequence is 0.98 (see score help below)

   1  MSDSPLSKRQKRKSAQEPELSLDQGDAEEDSQVENRVNLSENTPEPDLPA    50
  51  LEASYSKSYTPRKLVLSSGENRYAFSQPTNSTTTSLHVPNLQPPKTSSRG   100
 101  RDHKSYSQSPPRSPGRSPTRRLELLQLSPVKNSRVELQKIYDRHQSSSKQ   150
 151  QSRLFINELVLENFKSYAGKQVVGPFHTSFSAVVGPNGSGKSNVIDSMLF   200
 201  VFGFRANKMRQDRLSDLIHKSEAFPSLQSCSVAVHFQYVIDESSGTSRID   250
 251  EEKPGLIITRKAFKNNSSKYYINEKESSYTEVTKLLKNEGIDLDHKRFLI   300
 301  LQGEVENIAQMKPKAEKESDDGLLEYLEDIIGTANYKPLIEERMGQIENL   350
 351  NEVCLEKENRFEIVDREKNSLESGKETALEFLEKEKQLTLLRSKLFQFKL   400
 401  LQSNSKLASTLEKISSSNKDLEDEKMKFQESLKKVDEIKAQRKEIKDRIS   450
 451  SCSSKEKTLVLERRELEGTRVSLEERTKNLVSKMEKAEKTLKSTKHSISE   500
 501  AENMLEELRGQQTEHETEIKDLTQLLEKERSILDDIKLSLKDKTKNISAE   550
 551  IIRHEKELEPWDLQLQEKESQIQLAESELSLLEETQAKLKKNVETLEEKI   600
 601  LAKKTHKQELQDLILDLKKKLNSLKDERSQGEKNFTSAHLKLKEMQKVLN   650
 651  AHRQRAMEARSSLSKAQNKSKVLTALSRLQKSGRINGFHGRLGDLGVIDD   700
 701  SFDVAISTACPRLDDVVVDTVECAQHCIDYLRKNKLGYARFILLDRLRQF   750
 751  NLQPISTPENVPRLFDLVKPKNPKFSNAFYSVLRDTLVAQNLKQANNVAY   800
 801  GKKRFRVVTVDGKLIDISGTMSGGGNHVAKGLMKLGTNQSDKVDDYTPEE   850
 851  VDKIERELSERENNFRVASDTVHEMEEELKKLRDHEPDLESQISKAEMEA   900
 901  DSLASELTLAEQQVKEAEMAYVKAVSDKAQLNVVMKNLERLRGEYNDLQS   950
 951  ETKTKKEKIKGLQDEIMKIGGIKLQMQNSKVESVCQKLDILVAKLKKVKS  1000
1001  ASKKSGGDVVKFQKLLQNSERDVELSSDELKVIEEQLKHTKLALAENDTN  1050
1051  MNETLNLKVELKEQSEQLKEQMEDMEESINEFKSIEIEMKNKLEKLNSLL  1100
1101  TYIKSEITQQEKGLNELSIRDVTHTLGMLDDNKMDSVKEDVKNNQELDQE  1150
1151  YRSCETQDESEIKDAETSCDNYHPMNIDETSDEVSRGIPRLSEDELRELD  1200
1201  VELIESKINELSYYVEETNVDIGVLEEYARRLAEFKRRKLDLNNAVQKRD  1250
1251  EVKEQLGILKKKRFDEFMAGFNIISMTLKEMYQMITMGGNAELELVDSLD  1300
1301  PFSEGVTFSVMPPKKSWRNITNLSGGEKTLSSLALVFALHKYKPTPLYVM  1350
1351  DEIDAALDFRNVSIVANYIKERTKNAQFIVISLRNNMFELAQQLVGVYKR  1400
1401  DNRTKSTTIKNIDILNRT                                  1418

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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