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

NucPred

Fetching Q86UL8 from www.uniprot.org...

The NucPred score for your sequence is 0.93 (see score help below)

   1  MSKSLKKKSHWTSKVHESVIGRNPEGQLGFELKGGAENGQFPYLGEVKPG    50
  51  KVAYESGSKLVSEELLLEVNETPVAGLTIRDVLAVIKHCKDPLRLKCVKQ   100
 101  GGIVDKDLRHYLNLRFQKGSVDHELQQIIRDNLYLRTVPCTTRPHKEGEV   150
 151  PGVDYIFITVEDFMELEKSGALLESGTYEDNYYGTPKPPAEPAPLLLNVT   200
 201  DQILPGATPSAEGKRKRNKSVSNMEKASIEPPEEEEEERPVVNGNGVVVT   250
 251  PESSEHEDKSAGASGEMPSQPYPAPVYSQPEELKEQMDDTKPTKPEDNEE   300
 301  PDPLPDNWEMAYTEKGEVYFIDHNTKTTSWLDPRLAKKAKPPEECKENEL   350
 351  PYGWEKIDDPIYGTYYVDHINRRTQFENPVLEAKRKLQQHNMPHTELGTK   400
 401  PLQAPGFREKPLFTRDASQLKGTFLSTTLKKSNMGFGFTIIGGDEPDEFL   450
 451  QVKSVIPDGPAAQDGKMETGDVIVYINEVCVLGHTHADVVKLFQSVPIGQ   500
 501  SVNLVLCRGYPLPFDPEDPANSMVPPLAIMERPPPVMVNGRHNYETYLEY   550
 551  ISRTSQSVPDITDRPPHSLHSMPTDGQLDGTYPPPVHDDNVSMASSGATQ   600
 601  AELMTLTIVKGAQGFGFTIADSPTGQRVKQILDIQGCPGLCEGDLIVEIN   650
 651  QQNVQNLSHTEVVDILKDCPIGSETSLIIHRGGFFSPWKTPKPIMDRWEN   700
 701  QGSPQTSLSAPAIPQNLPFPPALHRSSFPDSTEAFDPRKPDPYELYEKSR   750
 751  AIYESRQQVPPRTSFRMDSSGPDYKELDVHLRRMESGFGFRILGGDEPGQ   800
 801  PILIGAVIAMGSADRDGRLHPGDELVYVDGIPVAGKTHRYVIDLMHHAAR   850
 851  NGQVNLTVRRKVLCGGEPCPENGRSPGSVSTHHSSPRSDYATYTNSNHAA   900
 901  PSSNASPPEGFASHSLQTSDVVIHRKENEGFGFVIISSLNRPESGSTITV   950
 951  PHKIGRIIDGSPADRCAKLKVGDRILAVNGQSIINMPHADIVKLIKDAGL  1000
1001  SVTLRIIPQEELNSPTSAPSSEKQSPMAQQSPLAQQSPLAQPSPATPNSP  1050
1051  IAQPAPPQPLQLQGHENSYRSEVKARQDVKPDIRQPPFTDYRQPPLDYRQ  1100
1101  PPGGDYQQPPPLDYRQPPLLDYRQHSPDTRQYPLSDYRQPQDFDYFTVDM  1150
1151  EKGAKGFGFSIRGGREYKMDLYVLRLAEDGPAIRNGRMRVGDQIIEINGE  1200
1201  STRDMTHARAIELIKSGGRRVRLLLKRGTGQVPEYDEPAPWSSPAAAAPG  1250
1251  LPEVGVSLDDGLAPFSPSHPAPPSDPSHQISPGPTWDIKREHDVRKPKEL  1300
1301  SACGQKKQRLGEQRERSASPQRAARPRLEEAPGGQGRPEAGRPASEARAP  1350
1351  GLAAADAADAARAGGKEAPRAAAGSELCRREGPGAAPAFAGPGGGGSGAL  1400
1401  EAEGRAGARAGPRPGPRPPGGAPARKAAVAPGPWKVPGSDKLPSVLKPGA  1450
1451  SAASR                                               1455

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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