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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