 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9NUA8 from www.uniprot.org...
The NucPred score for your sequence is 0.90 (see score help below)
1 MELPNYSRQLLQQLYTLCKEQQFCDCTISIGTIYFRAHKLVLAAASLLFK 50
51 TLLDNTDTISIDASVVSPEEFALLLEMMYTGKLPVGKHNFSKIISLADSL 100
101 QMFDVAVSCKNLLTSLVNCSVQGQVVRDVSAPSSETFRKEPEKPQVEILS 150
151 SEGAGEPHSSPELAATPGGPVKAETEEAAHSVSQEMSVNSPTAQESQRNA 200
201 ETPAETPTTAEACSPSPAVQTFSEAKKTSTEPGCERKHYQLNFLLENEGV 250
251 FSDALMVTQDVLKKLEMCSEIKGPQKEMIVKCFEGEGGHSAFQRILGKVR 300
301 EESLDVQTVVSLLRLYQYSNPAVKTALLDRKPEDVDTVQPKGSTEEGKTL 350
351 SVLLLEHKEDLIQCVTQLRPIMESLETAKEEFLTGTEKRVILNCCEGRTP 400
401 KETIENLLHRMTEEKTLTAEGLVKLLQAVKTTFPNLGLLLEKLQKSATLP 450
451 STTVQPSPDDYGTELLRRYHENLSEIFTDNQILLKMISHMTSLAPGEREV 500
501 MEKLVKRDSGSGGFNSLISAVLEKQTLSATAIWQLLLVVQETKTCPLDLL 550
551 MEEIRREPGADAFFRAVTTPEHATLETILRHNQLILEAIQQKIEYKLFTS 600
601 EEEHLAETVKEILSIPSETASPEASLRAVLSRAMEKSVPAIEICHLLCSV 650
651 HKSFPGLQPVMQELAYIGVLTKEDGEKETWKVSNKFHLEANNKEDEKAAK 700
701 EDSQPGEQNDQGETGSLPGQQEKEASASPDPAKKSFICKACDKSFHFYCR 750
751 LKVHMKRCRVAKSKQVQCKECSETKDSKKELDKHQLEAHGAGGEPDAPKK 800
801 KKKRLPVTCDLCGREFAHASGMQYHKLTEHFDEKPFSCEECGAKFAANST 850
851 LKNHLRLHTGDRPFMCKHCLMTFTQASALAYHTKKKHSEGKMYACQYCDA 900
901 VFAQSIELSRHVRTHTGDKPYVCRDCGKGFRQANGLSIHLHTFHNIEDPY 950
951 DCKKCRMSFPTLQDHRKHIHEVHSKEYHPCPTCGKIFSAPSMLERHVVTH 1000
1001 VGGKPFSCGICNKAYQQLSGLWYHNRTHHPDVFAAQNHRSSKFSSLQCSS 1050
1051 CDKTFPNTIEHKKHIKAEHADMKFHECDQCKELFPTPALLQVHVKCQHSG 1100
1101 SQPFRCLYCAATFRFPGALQHHVTTEHFKQSETTFPCELCGELFTSQAQL 1150
1151 DSHLESEHPKVMSTETQAAASQMAQVIQTPEPVAPTEQVITLEETQLAGS 1200
1201 QVFVTLPDSQASQASSELVAVTVEDLLDGTVTLICGEAK 1239
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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