 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q7S1Y0 from www.uniprot.org...
The NucPred score for your sequence is 0.77 (see score help below)
1 MSDDYDPTNINAASWEEQEDYGEADGSEQYGEAEGSEQQDIQHSSEHQEA 50
51 EYSVESNPNDLGDHPSQDGNTDDVGDDYDPASVVTSSVPAPPSAPAQEDS 100
101 KTAPQPAAPVAKKPRTAGGFLVGDSDDEDEDGDDDGEPQQQQQQQQQQQP 150
151 HQVVHKETGSGASSSGGSAPAPASASATAAPQSHSPAPQTATLTVQDNAG 200
201 ATTFNAPPVPQQVSHQSGATTAAVPTTPSSAAPAVDPTPVTQPAPDRVAI 250
251 YEDQIRDDPRGAMNAWLELMKEKRARNDIDGARQVYERFLAIFPQAADIW 300
301 VEYLDLELSLNNFPQAEGIFAKCLMTTPNVNLWTRYLDYIRRRNDLNDST 350
351 GQARQTVSQAYEFVIDNIGLDKDSGKIWAEYIQFIKFGPGTVGGSQWQDQ 400
401 QKMDQLRKAYQRAICVPISNVNTLWKEYDQFEMGLNKLTGRKYLSEKSPS 450
451 YMSAKSANTALEHITRGLNRTNLPRLPPAPGFDGDQEFMEQVEIWKKWIA 500
501 WEKSDPLDLKDDKDQPGLYQKRILYVYNQALMALRFWPEMWVDAAQWCFD 550
551 NNITTVENKVTKDGNANGVEFLIRGIEANPESVLLAFKHADHIESTYPIE 600
601 ENDEAKIQRGEAVKAPYNKVLDTLYAMIKSLKEKEAAQIAKLQEMTAAQE 650
651 SKAGSDNEDGDGAADNIKKAPIEAIQKGYAAQTQLLSRMISFVWIALIRA 700
701 MRRVQGKGGLNVPLGGMRKAFHDARARGRLTSDVYAAVAQLEWTIYKDPA 750
751 GGKIFDRGAKLFPEDENFTLENIKYLHSRDDHTNARVLFETVVNRLTQKP 800
801 ELVHKAKPLYQYFHKYESQFGELAQVTKLEKRMAELFPEDPKLAAFTARY 850
851 ASDKFDPITARIIVSPTTQLRPKNMIMPSIEQQQPQLPMSQRDTPAAGFS 900
901 PRPQGLKSPSAGPGAPFAPYAAKRPLDDRDYDDHPRKIARSEHDPFVRGA 950
951 SPLKGAAGRRLDQQRRMGGAAGAYSGSGAGSQVAPIARDITFLLSQIPRV 1000
1001 EFYDSHRLNPSRMVSLLQNVKVPEYLDWKRERERMQQMQQMQGDGYGGYG 1050
1051 GGGGGGGGGGYQGGGHARNISQDYAYRESPGPLGGRPLSPFTGGPGSRLA 1100
1101 SATAAYRQAPVGRPESSGSYEPPPAAQYGVPPPAQYDGGWAQQQQQQQYG 1150
1151 QPPAPQGYRYGNPPPPY 1167
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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