 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9UQB3 from www.uniprot.org...
The NucPred score for your sequence is 0.85 (see score help below)
1 MFARKPPGAAPLGAMPVPDQPSSASEKTSSLSPGLNTSNGDGSETETTSA 50
51 ILASVKEQELQFERLTRELEAERQIVASQLERCKLGSETGSMSSMSSAEE 100
101 QFQWQSQDGQKDIEDELTTGLELVDSCIRSLQESGILDPQDYSTGERPSL 150
151 LSQSALQLNSKPEGSFQYPASYHSNQTLALGETTPSQLPARGTQARATGQ 200
201 SFSQGTTSRAGHLAGPEPAPPPPPPPREPFAPSLGSAFHLPDAPPAAAAA 250
251 ALYYSSSTLPAPPRGGSPLAAPQGGSPTKLQRGGSAPEGATYAAPRGSSP 300
301 KQSPSRLAKSYSTSSPINIVVSSAGLSPIRVTSPPTVQSTISSSPIHQLS 350
351 STIGTYATLSPTKRLVHASEQYSKHSQELYATATLQRPGSLAAGSRASYS 400
401 SQHGHLGPELRALQSPEHHIDPIYEDRVYQKPPMRSLSQSQGDPLPPAHT 450
451 GTYRTSTAPSSPGVDSVPLQRTGSQHGPQNAAAATFQRASYAAGPASNYA 500
501 DPYRQLQYCPSVESPYSKSGPALPPEGTLARSPSIDSIQKDPREFGWRDP 550
551 ELPEVIQMLQHQFPSVQSNAAAYLQHLCFGDNKIKAEIRRQGGIQLLVDL 600
601 LDHRMTEVHRSACGALRNLVYGKANDDNKIALKNCGGIPALVRLLRKTTD 650
651 LEIRELVTGVLWNLSSCDALKMPIIQDALAVLTNAVIIPHSGWENSPLQD 700
701 DRKIQLHSSQVLRNATGCLRNVSSAGEEARRRMRECDGLTDALLYVIQSA 750
751 LGSSEIDSKTVENCVCILRNLSYRLAAETSQGQHMGTDELDGLLCGEANG 800
801 KDAESSGCWGKKKKKKKSQDQWDGVGPLPDCAEPPKGIQMLWHPSIVKPY 850
851 LTLLSECSNPDTLEGAAGALQNLAAGSWKWSVYIRAAVRKEKGLPILVEL 900
901 LRIDNDRVVCAVATALRNMALDVRNKELIGKYAMRDLVHRLPGGNNSNNT 950
951 ASKAMSDDTVTAVCCTLHEVITKNMENAKALRDAGGIEKLVGISKSKGDK 1000
1001 HSPKVVKAASQVLNSMWQYRDLRSLYKKDGWSQYHFVASSSTIERDRQRP 1050
1051 YSSSRTPSISPVRVSPNNRSASAPASPREMISLKERKTDYECTGSNATYH 1100
1101 GAKGEHTSRKDAMTAQNTGISTLYRNSYGAPAEDIKHNQVSAQPVPQEPS 1150
1151 RKDYETYQPFQNSTRNYDESFFEDQVHHRPPASEYTMHLGLKSTGNYVDF 1200
1201 YSAARPYSELNYETSHYPASPDSWV 1225
Positively and negatively influencing subsequences are coloured according to the following scale:
(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)
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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