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

NucPred

Fetching O75882 from www.uniprot.org...

The NucPred score for your sequence is 0.49 (see score help below)

   1  MVAAAAATEARLRRRTAATAALAGRSGGPHWDWDVTRAGRPGLGAGLRLP    50
  51  RLLSPPLRPRLLLLLLLLSPPLLLLLLPCEAEAAAAAAAVSGSAAAEAKE   100
 101  CDRPCVNGGRCNPGTGQCVCPAGWVGEQCQHCGGRFRLTGSSGFVTDGPG   150
 151  NYKYKTKCTWLIEGQPNRIMRLRFNHFATECSWDHLYVYDGDSIYAPLVA   200
 201  AFSGLIVPERDGNETVPEVVATSGYALLHFFSDAAYNLTGFNITYSFDMC   250
 251  PNNCSGRGECKISNSSDTVECECSENWKGEACDIPHCTDNCGFPHRGICN   300
 301  SSDVRGCSCFSDWQGPGCSVPVPANQSFWTREEYSNLKLPRASHKAVVNG   350
 351  NIMWVVGGYMFNHSDYNMVLAYDLASREWLPLNRSVNNVVVRYGHSLALY   400
 401  KDKIYMYGGKIDSTGNVTNELRVFHIHNESWVLLTPKAKEQYAVVGHSAH   450
 451  IVTLKNGRVVMLVIFGHCPLYGYISNVQEYDLDKNTWSILHTQGALVQGG   500
 501  YGHSSVYDHRTRALYVHGGYKAFSANKYRLADDLYRYDVDTQMWTILKDS   550
 551  RFFRYLHTAVIVSGTMLVFGGNTHNDTSMSHGAKCFSSDFMAYDIACDRW   600
 601  SVLPRPDLHHDVNRFGHSAVLHNSTMYVFGGFNSLLLSDILVFTSEQCDA   650
 651  HRSEAACLAAGPGIRCVWNTGSSQCISWALATDEQEEKLKSECFSKRTLD   700
 701  HDRCDQHTDCYSCTANTNDCHWCNDHCVPRNHSCSEGQISIFRYENCPKD   750
 751  NPMYYCNKKTSCRSCALDQNCQWEPRNQECIALPENICGIGWHLVGNSCL   800
 801  KITTAKENYDNAKLFCRNHNALLASLTTQKKVEFVLKQLRIMQSSQSMSK   850
 851  LTLTPWVGLRKINVSYWCWEDMSPFTNSLLQWMPSEPSDAGFCGILSEPS   900
 901  TRGLKAATCINPLNGSVCERPANHSAKQCRTPCALRTACGDCTSGSSECM   950
 951  WCSNMKQCVDSNAYVASFPFGQCMEWYTMSTCPPENCSGYCTCSHCLEQP  1000
1001  GCGWCTDPSNTGKGKCIEGSYKGPVKMPSQAPTGNFYPQPLLNSSMCLED  1050
1051  SRYNWSFIHCPACQCNGHSKCINQSICEKCENLTTGKHCETCISGFYGDP  1100
1101  TNGGKCQPCKCNGHASLCNTNTGKCFCTTKGVKGDECQLCEVENRYQGNP  1150
1151  LRGTCYYTLLIDYQFTFSLSQEDDRYYTAINFVATPDEQNRDLDMFINAS  1200
1201  KNFNLNITWAASFSAGTQAGEEMPVVSKTNIKEYKDSFSNEKFDFRNHPN  1250
1251  ITFFVYVSNFTWPIKIQIAFSQHSNFMDLVQFFVTFFSCFLSLLLVAAVV  1300
1301  WKIKQSCWASRRREQLLREMQQMASRPFASVNVALETDEEPPDLIGGSIK  1350
1351  TVPKPIALEPCFGNKAAVLSVFVRLPRGLGGIPPPGQSGLAVASALVDIS  1400
1401  QQMPIVYKEKSGAVRNRKQQPPAQPGTCI                       1429

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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