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

NucPred

Fetching Q03496 from www.uniprot.org...

The NucPred score for your sequence is 0.80 (see score help below)

   1  MTTDVQFSSQEIELFRVKEFLIANNPAKINNENKDAVLTQIEHDFRYLIQ    50
  51  YIKDGLPNLNESTRLIFPDTFSICLLRSHQIIASKKIDSQEFLSAVKEQL   100
 101  LTEANANIIFEYVLDFWADGGAPLMNALRDLFSKLLNLLKITYPMSTLKD   150
 151  VLFNWMNEILEVPSTLRVQYYLIDALSSDFDLYYIIEKKPHFIDNSFSLM   200
 201  NSDLLANSVGKCIVSLLLNIYEKHFKKNESFVQEWIQLWKSCALKYIHDK   250
 251  QYTKSINLYIMIPLFKNMPNSAFTLFLECMSNKDPSLLLSLLKIGQELGI   300
 301  EEEPFCDNKYTTVDSVNKLIEQDEYKLQVFEILTFSTKKSKPIRPFVFKT   350
 351  IKQYLYVFFVDTELERRNYFCSSMKHFIFRTRDCAYSLARDARKLKKAEK   400
 401  FPDEQREKLAQVEEARAFLVWLCNFIKYNLAPGTLYQANVTSLKLMHILI   450
 451  KSGVDKSTPQKFLDNQNKREYPFSIPILQDVTFLRLLIDLLVSNYADVRE   500
 501  LSKEMLFIMISADESRGLFLDTLDANALKWTATSLLSDYEKGDAGATVYE   550
 551  FIFTVMGSQRSFIDQTIDILAQMVQNLQNDSIGCAENSIGPHFAALSLIL   600
 601  NKFNSEENHQDTSKIISKLINLVLKSWEATRNVVCHDSAHGILPEKYANC   650
 651  GVPDQVIISHAFRAIKEASYLLETILKKYPLTRDQLDSIGDLFIVQLSTI   700
 701  RHSGAFQAVLPGLKAFCIRCQLEFPAILEELLSKSVKSLKSKTQHITRRS   750
 751  GGLPFLVTTVLSAEVTKGRPLLQKTFENLLLVARLPIPPHQDEFDLPQVN   800
 801  AINCINAIFVEPKLSVHCTSFVSEALELALLNFDCDIWALRNCSIMLFTS   850
 851  LQNRIFGKVGRSVSAKLFFTKYSGLRQLLLNILNSSIAQYSGSERKSYQI   900
 901  ESIFLVLNVLLRLRPTAGYTGLKEFNVSVYECLSNENWKIRDMASRVLHM   950
 951  LSENFEEEIRKLLDLASIAKQNQLHGHLLALQQLVPQYLSGTRDMELIQR  1000
1001  ILEKKRMLLLENKCFITKKAYLKLTCCILETCDIPDSILKDYISTLRNTF  1050
1051  IAENNEYVVDGSKQLYLAQILDMLLKYEDSIYLDDICLLGLYSPFYEAQL  1100
1101  STLQYMNTNFHWETTRNSEFLEQLQLLLRVPDLLPMAKALVVKILSRKKN  1150
1151  TLSLTTCTDLLKTNNSEDTKLAAVSSLSAKLSSQTFHQVWNLLQGFFADS  1200
1201  CSKDFRLASLECLTAYPESCKNSRILLQLYNFLWDDDSEIREKASFYLNK  1250
1251  NFIQTADWEYNRNTSVTALIFTKKFVDVFTSSEVVEELCLQLFQYLNEYD  1300
1301  MFAAEESAKNCLFTIEKDNQFINELQKAMHILNMIKLTGRDISKCYKDQI  1350
1351  HHLKSALLEHFNTEDFKDSPLGWCSNAEIFSRITLLKELIQHYSPSDYEN  1400
1401  FINVLTKHSVHPLIISYSQL                                1420

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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