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

NucPred

Fetching Q13428 from www.uniprot.org...

The NucPred score for your sequence is 0.92 (see score help below)

   1  MAEARKRRELLPLIYHHLLRAGYVRAAREVKEQSGQKCFLAQPVTLLDIY    50
  51  THWQQTSELGRKRKAEEDAALQAKKTRVSDPISTSESSEEEEEAEAETAK   100
 101  ATPRLASTNSSVLGADLPSSMKEKAKAETEKAGKTGNSMPHPATGKTVAN   150
 151  LLSGKSPRKSAEPSANTTLVSETEEEGSVPAFGAAAKPGMVSAGQADSSS   200
 201  EDTSSSSDETDVEGKPSVKPAQVKASSVSTKESPARKAAPAPGKVGDVTP   250
 251  QVKGGALPPAKRAKKPEEESESSEEGSESEEEAPAGTRSQVKASEKILQV   300
 301  RAASAPAKGTPGKGATPAPPGKAGAVASQTKAGKPEEDSESSSEESSDSE   350
 351  EETPAAKALLQAKASGKTSQVGAASAPAKESPRKGAAPAPPGKTGPAVAK   400
 401  AQAGKREEDSQSSSEESDSEEEAPAQAKPSGKAPQVRAASAPAKESPRKG   450
 451  AAPAPPRKTGPAAAQVQVGKQEEDSRSSSEESDSDREALAAMNAAQVKPL   500
 501  GKSPQVKPASTMGMGPLGKGAGPVPPGKVGPATPSAQVGKWEEDSESSSE   550
 551  ESSDSSDGEVPTAVAPAQEKSLGNILQAKPTSSPAKGPPQKAGPVAVQVK   600
 601  AEKPMDNSESSEESSDSADSEEAPAAMTAAQAKPALKIPQTKACPKKTNT   650
 651  TASAKVAPVRVGTQAPRKAGTATSPAGSSPAVAGGTQRPAEDSSSSEESD   700
 701  SEEEKTGLAVTVGQAKSVGKGLQVKAASVPVKGSLGQGTAPVLPGKTGPT   750
 751  VTQVKAEKQEDSESSEEESDSEEAAASPAQVKTSVKKTQAKANPAAARAP   800
 801  SAKGTISAPGKVVTAAAQAKQRSPSKVKPPVRNPQNSTVLARGPASVPSV   850
 851  GKAVATAAQAQTGPEEDSGSSEEESDSEEEAETLAQVKPSGKTHQIRAAL   900
 901  APAKESPRKGAAPTPPGKTGPSAAQAGKQDDSGSSSEESDSDGEAPAAVT   950
 951  SAQVIKPPLIFVDPNRSPAGPAATPAQAQAASTPRKARASESTARSSSSE  1000
1001  SEDEDVIPATQCLTPGIRTNVVTMPTAHPRIAPKASMAGASSSKESSRIS  1050
1051  DGKKQEGPATQVSKKNPASLPLTQAALKVLAQKASEAQPPVARTQPSSGV  1100
1101  DSAVGTLPATSPQSTSVQAKGTNKLRKPKLPEVQQATKAPESSDDSEDSS  1150
1151  DSSSGSEEDGEGPQGAKSAHTLGPTPSRTETLVEETAAESSEDDVVAPSQ  1200
1201  SLLSGYMTPGLTPANSQASKATPKLDSSPSVSSTLAAKDDPDGKQEAKPQ  1250
1251  QAAGMLSPKTGGKEAASGTTPQKSRKPKKGAGNPQASTLALQSNITQCLL  1300
1301  GQPWPLNEAQVQASVVKVLTELLEQERKKVVDTTKESSRKGWESRKRKLS  1350
1351  GDQPAARTPRSKKKKKLGAGEGGEASVSPEKTSTTSKGKAKRDKASGDVK  1400
1401  EKKGKGSLGSQGAKDEPEEELQKGMGTVEGGDQSNPKSKKEKKKSDKRKK  1450
1451  DKEKKEKKKKAKKASTKDSESPSQKKKKKKKKTAEQTV              1488

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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