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

NucPred

Fetching P13433 from www.uniprot.org...

The NucPred score for your sequence is 0.67 (see score help below)

   1  MLRPAYKSLVKTSLLQRRLISSKGSKLFKPSPDSTSTILISEDPLVTGSS    50
  51  PTSSTTSGIISSNDFPLFNKNRKDAKSSISYQWKNPSELEFDPFNKSHAS   100
 101  AVTSMTRTRDVMQLWSLLEACLQSNLMKRAFSILESLYLVPEHKQRFIED   150
 151  YNMYLNSFSKNDPNFPILKMNEKLTNDLETSFKDVNYNDKTLAIMIHHAL   200
 201  NFHSTTSSMLLKPIISAYLKMSVNGIREIFSCLDILTISDLNILMNDLKV   250
 251  ITPSQLPNSVRPILESLTLSPTPVNNIENEEGLNKVEAENDSKLHKASNA   300
 301  SSDSIKKPSLDPLREVSFHGSTEVLSKDAEKLIAVDTIGMRVIRHTLLGL   350
 351  SLTPEQKEQISKFKFDANDNVLKMKPTKNDDNNNSINFFEIYNSLPTLEE   400
 401  KKAFESALNIFNQDRQKVLENRATEAARERWKHDFEEAKARGDISIEKNL   450
 451  NVKLWKWYNEMLPLVKEEINHCRSLLSEKLSDKKGLNKVDTNRLGYGPYL   500
 501  TLIDPGKMCVITILELLKLNSTGGVIEGMRTARAVISVGKAIEMEFRSEQ   550
 551  VLKSESQAFRDVNKKSPEFKKLVQNAKSVFRSSQIEQSKILWPQSIRARI   600
 601  GSVLISMLIQVAKVSVQGVDPVTKAKVHGEAPAFAHGYQYHNGSKLGVLK   650
 651  IHKTLIRQLNGERLIASVQPQLLPMLVEPKPWVNWRSGGYHYTQSTLLRT   700
 701  KDSPEQVAYLKAASDNGDIDRVYDGLNVLGRTPWTVNRKVFDVVSQVWNK   750
 751  GEGFLDIPGAQDEMVLPPAPPKNSDPSILRAWKLQVKTIANKFSSDRSNR   800
 801  CDTNYKLEIARAFLGEKLYFPHNLDFRGRAYPLSPHFNHLGNDMSRGLLI   850
 851  FWHGKKLGPSGLKWLKIHLSNLFGFDKLPLKDRVAFTESHLQDIKDSAEN   900
 901  PLTGDRWWTTADKPWQALATCFELNEVMKMDNPEEFISHQPVHQDGTCNG   950
 951  LQHYAALGGDVEGATQVNLVPSDKPQDVYAHVARLVQKRLEIAAEKGDEN  1000
1001  AKILKDKITRKVVKQTVMTNVYGVTYVGATFQIAKQLSPIFDDRKESLDF  1050
1051  SKYLTKHVFSAIRELFHSAHLIQDWLGESAKRISKSIRLDVDEKSFKNGN  1100
1101  KPDFMSSVIWTTPLGLPIVQPYREESKKQVETNLQTVFISDPFAVNPVNA  1150
1151  RRQKAGLPPNFIHSLDASHMLLSAAECGKQGLDFASVHDSYWTHASDIDT  1200
1201  MNVVLREQFIKLHEVDLVLRLKEEFDQRYKNYVKIGKLKRSTDLAQKIIR  1250
1251  IRKDLSRKLGRSTTLADEIYFEKKRQELLNSPLIEDRNVGEKMVTTVSLF  1300
1301  EDITDLDALELENGGDENSGMSVLLPLRLPEIPPKGDFDVTVLRNSQYFF  1350
1351  S                                                   1351

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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