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

NucPred

Fetching Q99J86 from www.uniprot.org...

The NucPred score for your sequence is 0.42 (see score help below)

   1  MVAAAAAAEATEARLRGYTTATAAPAGWKERQHRPCAATGAWRPWPRAGL    50
  51  CLPRVLSRALSPPPLLPLLPLLFSLLLLPLPREAEAAAVAAAVSGSAAAE   100
 101  AKECDRPCVNGGRCNPGTGQCVCPTGWVGEQCQHCGGRFRLTGSSGFVTD   150
 151  GPGNYKYKTKCTWLIEGQPNKIMRLRFNHFATECSWDHLYVYDGDSIYAP   200
 201  LIAAFSGLIVPERDGNETAPEVTVTSGYALLHFFSDAAYNLTGFNITYNF   250
 251  DMCPNNCSGRGECKSSNSSSTVECECSENWKGESCDIPHCTDNCGFPHRG   300
 301  ICNASDTRGCSCFPHWQGPGCSIPVPANQSFWTREEYSDLKLPRASHKAV   350
 351  VNGNIMWVVGGYMFNHSDYSMVLAYDLASREWLSLNHSVNSVVVRYGHSL   400
 401  ALHKDKIYMYGGKIDSTGNVTNELRVFHIHNESWVLLTPKAKDQYAVVGH   450
 451  SAHIVTLSSGRVVMLVIFGHCPLYGYISVVQEYDLEKNTWSILQTQGALV   500
 501  QGGYGHSSVYDHRTKALYVHGGYKAFSANKYRLADDLYRYHVDTQMWTIL   550
 551  KDSRFFRYLHTAVIVSGTMLVFGGNTHNDTSMSHGAKCFSSDFMAYDIAC   600
 601  DRWSVLPRPELHHDVNRFGHSAVLHNSTMYVFGGFNSLLLSDVLVFTSEQ   650
 651  CDAHRSEAACVAAGPGIRCLWDTQSSRCTSWELATEEQAEKLKSECFSKR   700
 701  TLDHDRCDQHTDCYSCTANTNDCHWCNDHCVPVNHSCTEGQISIAKYDNC   750
 751  PKDNPMYYCNKKTSCRSCALDQNCQWEPRNQECIALPENICGIGWHLVGN   800
 801  SCLKITTAKENYDNAKLSCRNHNAFLASLTSQKKVEFVLKQLRLMQSSQS   850
 851  TSKLTLTPWVGLRKINVSYWCWEDMSPFTNSLLQWMPSEPSDAGFCGILS   900
 901  EPSTRGLKAATCINPLNGSVCERPANHSAKQCRTPCALRTACGECTSSSS   950
 951  ECMWCSNMKQCVDSNAYVASFPFGQCMEWYTMSSCPPENCSGYCTCSHCL  1000
1001  EQPGCGWCTDPSNTGKGKCIEGSYKGPVKMPSHASTGNVYPQPLLNSSMC  1050
1051  LEDSRYNWSFIHCPACQCNGHSKCINQSICEKCEDLTTGKHCETCISGFY  1100
1101  GDPTNGGKCQPCKCNGHASLCNTNTGKCFCTTKGVKGEECQLCEVENRYQ  1150
1151  GNPLKGTCYYTLLIDYQFTFSLSQEDDRYYTAINFVATPDEQNRDLDMFI  1200
1201  NASKNFNLNITWATSFPAGTQTGEEVPVVSKTNIKEYKDSFSNEKFDFRN  1250
1251  HPNITFFVYVSNFTWPIKIQIAFSQHSNFMDLVQFFVTFFSCFLSLLLVA  1300
1301  AVVWKIKQSCWASRRREQLLREMQQMASRPFASVNVALETDEEPPDLIGG  1350
1351  SIKTVPKPIALEPCFGNKAAVLSVFVRLPRGLGGIPPPGQSGLAVASALV  1400
1401  DISQQMPIVYKEKSGAVRNRKQQPPAQPGTCI                    1432

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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