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

NucPred

Fetching Q9THV5 from www.uniprot.org...

The NucPred score for your sequence is 0.86 (see score help below)

   1  MEVLMAERANLVFHNKVIDGTAIKRLISRLIDHFGMAYTSHILDQVKTLG    50
  51  FQQATATSISLGIDDLLTIPSKGWLVQDAEQQSLILEKHHHYGNVHAVEK   100
 101  LRQSIEIWYATSEYLRQEMNPNFRMTDPFNPVHMMSFSGARGNASQVHQL   150
 151  VGMRGLMSDPQGQMIDLPIQSNLREGLSLTEYIISCYGARKGVVDTAVRQ   200
 201  SDAGYLTRRLVEVVQHIVVRRTDCGTIRGISVSPRNKSRMMSERIFIQTL   250
 251  IGRVLADDIYIGSRCVAFRNQDLGIGLVNRFITFGTQPISIRTPFTCRST   300
 301  SWICRLCYGRSPTHGDLVELGEAVGIIAGQSIGEPGTQLTLRTFHTGGVF   350
 351  TGGTAEHVRAPYNGKIKFNEDLVHSTRTRHGHPAFLCYIDLSVIIESEDI   400
 401  IHSVTIPPKSFLLVQNDQYVESEQVIAEIREGTYTFQFKERVRKYIYSDS   450
 451  EGGMHWSTDVSHAPEFTYSNVHLLPKTSHLWILSGGSCGSSLILFSIHKD   500
 501  QDQMNIPFLSVERKSISSLSVNNDQVSQKFFSSDFSDKKILIPNYSELNG   550
 551  IVGTSHYNFIYSAIFHENSDLLAKRRRNRFLIPFQSIQEQEQEKEFIPHS   600
 601  GISVEIPINGIFRRNSIFAFFDDPRYRRKSSGILKYGTLKADSIIQKEDM   650
 651  IEYRGVQKFKTKYEMKVDRFFFIPEEVHILPESSAIMVENYSIIGVDTRI   700
 701  TLNIRSQVGGLIRVERKKKRIELKIFSGDIHFPDKTDKISRHSGILIPPG   750
 751  RGKTNSKESKIVKNWIYVQRITPTKKKFFVLVRPVATYEIADSINLATLF   800
 801  PKDLFREKDNIQLRVFNYILYGNGKPTRGISDTSIQLVRTCLVLNWDQDN   850
 851  KNSSLEEVRAFFVEVNTKGLIRDFIRIGLVKSHISYIRKRNNPSSEKKEG   900
 901  SDHSMNPFYSISPKAGILHQSLRQNHGTIRMFLNRNRNPILLILSSSNCF   950
 951  RIGPFNHVKYHNVINQSIKKKTSNYIKNCRAPYGTAIQILIFIHFAFTKL  1000
1001  INQISCIKYLHLQTSNVFFPVIHSYLIDENGRIFNLDPYSNLVLNPFKLN  1050
1051  WYFLHQNYNNNYCEETSTIISLGQFFCENVCIAKKEPYLKSGQVLIVQRD  1100
1101  SVVIRSAKPYLATPGAKVHGHYREILYEGDTLVTFIYEKSRSGDITQGLP  1150
1151  KVEQVLEVRSIDSISLNLEKRIKGWNRCITRILGIPWGFLIGAELTIVQS  1200
1201  RISLVNKIKQVYRSQGVQIHNRHIEIIVRQITSKVLVSEEGMSNVFLPGE  1250
1251  LIGLLRAERTGRALEEAICYRAVLLGITRASLNTQSFISEASFQETARVL  1300
1301  AKAALRGRIDWLKGLKENVVLGGVIPPGPGSQRIGALSTATYQHSFGKNK  1350
1351  NYLIRGRYERYFILPQGILCLFYQIQNLPFLELH                  1384

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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