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

NucPred

Fetching P34501 from www.uniprot.org...

The NucPred score for your sequence is 0.87 (see score help below)

   1  MWTARHAVALLVVLTYAYSSILPPGTTFVQSIRDIFRFQEQLKKENVEDT    50
  51  ICSETPPESSIPNRDELLELIRKSKIEDHKFDEHVRKKRQLSRISYQEYL   100
 101  DNLGKADYDVRIEEGWTEILYPFGTWAMDKQLMGQAGRETQTNLGFDCPF   150
 151  FGFRFNYTMVYPMGMLSFGLPPFSAPPWTFPNPAWPKQRDHSFVAAFYAD   200
 201  AMFQWIGNTKISNVFFRSVHRPRLDDDEVYERNSQTNYGAPNYQQAGAQS   250
 251  AANQQFSNPSQYSQNLNAYSQNQQYNTQLLQQQQQIYGKRKKRQMPGRVS   300
 301  QPGMVVDPWLLDNITRHIQDGYTGANGFRAEHAFIATWYRMAHGGAARAL   350
 351  DVSQFEHVKDWQNTFQVVLASDEIRTFAIFNYARLNWTSSNEAGGLDGFG   400
 401  GKQAAMAGFNGGNGTGWYGLPYSGEGRLWKLGYFSNVLTPGRWIHRVDEV   450
 451  IIPAGCTNASNGGMMTAPPWGPMHGGMAINVSGPCLRPADSVKVNFENWQ   500
 501  TSCTRLSRVRARCIMPMFHKIGLVPIRMSRDGGQSFPFFGKFYVVNSERA   550
 551  PASVSLKDSVDNKTNRWYEPYAQELALGWQAMNLTWNTGARVDISLFGYW   600
 601  EDADRSHFERIDYLARGISNTGSYSFRPQQLTKQFLLRDAWQKFHFGFVQ   650
 651  VALADAEDGVMWSKPTPFPWYHLHEWERYYGRNWPIDMCIEWFEYDGKRN   700
 701  NFQIDLTTDFPCPCKLPQAMLDLGRFMPIMDCDKDGDTSCPFNKGAQHCI   750
 751  QSVQPTFSGSSQQCCYDYDGYLMFTDDWEPDGDYTTFFQPGTPARAHRYG   800
 801  AAPYRLPPFIPTLSNYQLDLNPYRTCCKYADHCEFYYWRRMTNGCQDYRA   850
 851  PAAGYIYGEPHVITYDGIRYTMPGKGYYVLTMSDSPYHKLMVQVRLEQPD   900
 901  DTLWHAHVNATVITGVAVQENDSSIVQVYARKPMRRWRYRTDVYVDGTRR   950
 951  FFDKPHWKHQQFKHLDIRNPLQNMNQSEIVIMLKSGVGIRIFEGFGMLDV  1000
1001  MVTLPPSYNTTCRPGESLSSSLNAPRGQRRCYTTLGLLGTYNNDPADDLT  1050
1051  TPSGTVTRVQNPTTTASTTQMIYEQFASFWKIDGTNDKIGGVLFQDKFKP  1100
1101  IYNPLLFAESDYRPVYWPQTIDMNASRVFTMEQVVSTCQNNPECEYDFIM  1150
1151  TGRKEVGLTTLRRQKEFFALQKTGSKQLISCGPLLKKEGVVKTPPAANYL  1200
1201  DGDKVVFSCKPKYYIHGDIERVCRNGTWSPGWWAWCRDRNLEYALKWMTA  1250
1251  LLSIFGISLIFVIFFCILWNIRKKKQAAHAERLQLKEQSDRLNKLENERI  1300
1301  FGTSPEKTPLIETDFRSNFNMNQPSRPIPSQPPSSQYSPPVFAAPPPPSQ  1350
1351  PTRLPTYTNAISQQQRQFEPPRPPRGNMRFETSAI                 1385

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.