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

NucPred

Fetching P19598 from www.uniprot.org...

The NucPred score for your sequence is 0.78 (see score help below)

   1  MKIIFFLCSFLFFIINTQCVTHESYQELVKKLEALEDAVLTGYSLFQKEK    50
  51  MVLKDGANTQVVAKPADAVSTQSAKNPPGATVPSGTASTKGAIRSPGAAN   100
 101  PSDDSSDSDAKSYADLKHRVQNYLFTIKELKYPELFDLTNHMLTLCDNIH   150
 151  GFKYLIDGYEEINELLYKLNFYFDLLRAKLNDVCANDYCQIPFNLKIRAN   200
 201  ELDVLKKLVFGYRKPLDFIKDNVGKMEDYIKKNKTTIANINELIEGSKKT   250
 251  IDQNKNADNEEGKKKLYQAQYDLFIYNKQLQEAHNLISVLEKRIDTLKKN   300
 301  ENIKKLLEDIDKIKIDAEKPTTGVNQILSLRLEKESRHEEKIKEIAKTIK   350
 351  FNIDRLFTDPLELEYYLREKNKKVDVTPKSQDPTKSVQIPKVPYPNGIVY   400
 401  PLPLTDIHNSLAADNDKNSYGDLMNPHTKEKINEKIITDNKERKIFINNI   450
 451  KKQIDLEEKNINHTKEQNKKLLEDYEKSKKDYEELLEKFYEMKFNNNFNK   500
 501  DVVDKIFSARYTYNVEKQRYNNKFSSSNNSVYNVQKLKKALSYLEDYSLR   550
 551  KGISEKDFNHYYTLKTGLEADIKKLTEEIKSSENKILEKNFKGLTHSANA   600
 601  SLEVSDIVKLQVQKVLLIKKIEDLRKIELFLKNAQLKDSIHVPNIYKPQN   650
 651  KPEPYYLIVLKKEVDKLKEFIPKVKDMLKKEQAVLSSITQPLVAASETTE   700
 701  DGGHSTHTLSQSGETEVTEETEETVGHTTTVTITLPPKEVKVVENSIEHK   750
 751  SNDNSQALTKTVYLKKLDEFLTKSYICHKYILVSNSSMDQKLLEVYNLTP   800
 801  EENELKSCDRLDLLFNIQNNIPAMYSLYDSMNNDLQHLFFELYQKEMIYY   850
 851  LHKLKEENHIKKLLEEPKQITGTSSTSSPGNTTVNTAQSATHSNSQNQQS   900
 901  NASSTNTQNGVAVSSGPAVVEESHDPLTVLSISNDLKGIVSLLNLGNKTK   950
 951  VPNPLTISTTEMEKFYENILKIMIPIFNDDIKQFVKSNSKVITGLTETQK  1000
1001  NALNDEIKKLKDTLQLSFDLYNKYKLKLDRLFNKKKELGQDKMQIKKLTL  1050
1051  LKEQLESKLNSLNNPHNVLQNFSVFFNKKKEAEIAETENTLENTKILLKH  1100
1101  YKGLVKYYNGESSPLKTLSEVSIQTEDNYANLEKFRVLSKIDGKLNDNLH  1150
1151  LGKKKLSFLSSGLHHLITELKEVIKNKNYTGNSPSENNKKVNEALKSYEN  1200
1201  FLPEAKVTTVVTPPQPDVTPSPLSVRVSGSSGSTKEETQIPTSGSLLTEL  1250
1251  QQVVQLQNYDEEDDSLVVLPIFGESEDNDEYLDQVVTGEAISVTMDNILS  1300
1301  GFENEYDVIYLKPLAGVYRSLKKQIEKNIFTFNLNLNDILNSRLKKRKYF  1350
1351  LDVLESDLMQFKHISSNEYIIEDSFKLLNSEQKNTLLKSYKYIKESVEND  1400
1401  IKFAQEGISYYEKVLAKYKDDLESIKKVIKEEKEFPSSPPTTPPSPAKTD  1450
1451  EQKKESKFLPFLTNIETLYNNLVNKIDDYLINLKAKINDCNVEKDEAHVK  1500
1501  ITKLSDLKAIDDKIDLFKNPYDFEAIKKLINDDTKKDMLGKLLSTGLVQN  1550
1551  FPNTIISKLIEGKFQDMLNISQHQCVKKQCPQNSGCFRHLDEREECKCLL  1600
1601  NYKQEGDKCVENPNPTCNENNGGCDADAKCTEEDSGSNGKKITCECTKPD  1650
1651  SYPLFDGIFCSSSNFLGISFLLILMLILYSFI                    1682

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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