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

NucPred

Fetching Q9M8D3 from www.uniprot.org...

The NucPred score for your sequence is 0.27 (see score help below)

   1  MNTSQATRAALFLNGSNRQAMLLQRSSMSQLWGSVRMRTSRLSLNRTKAV    50
  51  SLRCSAQPNKPKAAVSTGSFVTADELPSLVEKPAAEVIHFYRVPLIQESA   100
 101  NAELLKAVQTKISNQIVSLTTEQSFNIGLESKLKDEKLSVLKWILQETYE   150
 151  PENLGTDSFLERKKQEGLHAVIVEVGPRLSFTTAWSTNAVSICRACGLDE   200
 201  VTRLERSRRYLLFSKEPLLENQIKEFAAMVHDRMTECVYTQKLVSFETNV   250
 251  VPEEVKYVPVMEKGRKALEEINQEMGLAFDEQDLQYYTRLFREDIKRDPT   300
 301  NVELFDIAQSNSEHSRHWFFAGNMVIDGKPMDKSLMQIVKSTWEANRNNS   350
 351  VIGFKDNSSAIRGFLVNQLRPLLPGSVCLLDVSARDLDILFTAETHNFPC   400
 401  AVAPYPGAETGAGGRIRDTHATGRGSFVVASTSGYCVGNLNMEGSYAPWE   450
 451  DSSFQYPSNLASPLQILIDASNGASDYGNKFGEPMIQGYTRTFGMRLPSG   500
 501  DRREWLKPIMFSAGIGQIDHTHITKGEPEVGMLVVKIGGPAYRIGMGGGA   550
 551  ASSMVSGQNDAELDFNAVQRGDAEMSQKLYRVVRACIEMGEKNPIISIHD   600
 601  QGAGGNCNVVKEIIYPQGAEIDIRAVVVGDHTMSVLEIWGAEYQEQDAIL   650
 651  VKAESREILQSICKRERLSMAVIGTINGGGRCTLIDSTAAAKCSKEGLPP   700
 701  PPPAVDLELEKVLGDMPKKTFKFNRIAYAREPLDIAPGITLMDALKRVLR   750
 751  LPSVSSKRFLTTKVDRCVTGLVAQQQTVGPLQITLADVAVIAQTFTDLTG   800
 801  GACAIGEQPIKGLLDPKAMARLAVGEALTNLVWAKVTALSDVKASGNWMY   850
 851  AAKLEGEGSAMYDAAIALSEAMIELGIAIDGGKDSLSMAAHADGEVVKAP   900
 901  GNLVISAYVTCPDITKTVTPDLKLGGDDGILLHVDLAKGKRRLGGSALAQ   950
 951  VFGQIGNDCPDLDDVPYLKNVFDGVQALIAENLVSAGHDISDGGLVVTAL  1000
1001  EMAFAGNKGINLDLASNGISLFETLFSEELGLVLEISKTNLDAVMEKLRA  1050
1051  FDVTAEIIGNVTDSPLIEVKVDGITHLSEKTSFLRDMWEDTSFQLEKLQR  1100
1101  LASCVEMEKEGLKFRHEPNWKLSFIPSSTNNNYMSQDVKPKVAVIREEGS  1150
1151  NGDREMSAAFYAAGFEPWDVTVSDLLAGDITLDQFRGIVFVGGFSYADVL  1200
1201  DSAKGWAASIRFNEPVLSQFQEFYKRPDTFSLGICNGCQLMALLGWVPGP  1250
1251  QVGGSLDTSQPRFVHNESGRFECRFTSVTIKDSPSIMLKGMEGSTLGVWA  1300
1301  AHGEGRAYFPDEGVLDHMLHSDLAPLRYCDDDGNVTEAYPFNLNGSPLGI  1350
1351  AAICSPDGRHLAMMPHPERCFLMWQFPWYPTSWDVEKAGPSPWLKMFQNA  1400
1401  RDWLESC                                             1407

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.)

Go back to the NucPred Home Page.