 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8QHJ8 from www.uniprot.org...
The NucPred score for your sequence is 0.61 (see score help below)
1 MASEEASLRALESLMTEFFHSCTTNDRKREIEELLNSFAGQPGSWRHWLY 50
51 FLSNSRNEYVMMYSLTVFENLVNKMWVGVASEDKAELRSCLPKLLLSQHA 100
101 LLPFFIRNKLCKVIVDIGRQDWPMFYHDFFSNTLQLVQSPSLASLGLVLL 150
151 KMTSEELVCPREDLSVARKDELKKLLLDQIPTVLNLLTRILETVWDKHSV 200
201 TVTTPPPSPTSRESGVMLGDSTPMVLDAESGALCLLALECLAHLFSWIPL 250
251 SSSITPSLLASIFHFARFGCQQPIKTKPLPTSNGDSAPGSLPANGGGHCR 300
301 TGQIVGHAERARLGVMAMNCINELMCKNCVPVDFEEFLLRMFQQTFYLLQ 350
351 RLTNTHSHTNTHTIKSRLQDLDESYVEKFTDFLRLFVSVHLRRIESNAQF 400
401 PLVEFLALLFKYTFNQPSHEGYLACLDIWSVFLDYLTTKIRSRLADRDSV 450
451 INRYKDALVLLLREVLNRIQFRLNQSQLEELDDETLDDDQQTEWQRYLRQ 500
501 SLEVVARVMELLPSQTFSVLFPVLQEDLDVYLGLQQFIVRSGTSRRLNIT 550
551 AEADCRKLHCALRDLSSLLQAVGRLAEFFTGDVFTARFNDALAIVQRLVE 600
601 VSCYGSQISLYDVEMAVPSVLKPDLIDVHAQSLAALQAYSHWLAQFCGEV 650
651 QRQQDQTQFVDLITSSMAAASPLINGKVPEKLLLSACHLLVSMATTVRPV 700
701 FLVSLPAVQNIFNLITENHNHRLPQEAHVLVCRALSNMLLLPWPSLPEGE 750
751 QQWPNRSANHARLISSLTQQYRLLPRPPNHHHTSKAVIQQTLCVLRDLVD 800
801 SISGEATKSRQICYHSLQESVQVSLALFPLFIQQPEVTDEMLSFFLTLFQ 850
851 ALRVQMGVAFTEQIIQTFLSMFTREQLAVGILQEGSSGSKVVQKFLKILQ 900
901 VVVQEPGQTFKPLLPSILSLCLDQVYPIVAERSCPDVRAEMFELLFQILH 950
951 QNWRFFFKSSVLSSVQRSGAEELMENQAQFTAAMQAFGQSFLQPDIHIFK 1000
1001 QNLSYLEVLNTKHKLYHRKLFRNAMLFHFINVLLQVLLHKSHDLLQEDIT 1050
1051 LALYNMAAVDFSAFYSSFLPEFLNGCQGLDPHQRTTLARNFTPERDLPSF 1100
1101 SQGVYRIVNDLRFYRLCNGSLPPGTLKL 1128
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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