 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9EPE9 from www.uniprot.org...
The NucPred score for your sequence is 0.32 (see score help below)
1 MAVVGNAVPCGARPGGARDNGSPQPGSRLRPGLAAGPALIANGDELVAAV 50
51 WPYRRLALLRRLTVLPFAGLLYPAWLGAAASGCWGWGSSWTQIPEAALLA 100
101 LATICLAHALTVLSGHWSVHAHCALTCTPEYDPNKVTFVKVVPTPNNGST 150
151 ELVALHRDKGEDGLEVLSFEFQKIKYSYDALEKKQFLPVAFPVGNAFSYY 200
201 QSNRGFQEDSEIRAAEKKFGSNKAEMVVPDFSELFKERATAPFFVFQVFC 250
251 VGLWCLDEYWYYSVFTLSMLVAFEASLVQQQMRNMSEIRKMGNKPHMIQV 300
301 YRSRKWRPVASDDIVPGDIVSIGRSPQENLVPCDVLLLRGRCIVDEAMLT 350
351 GESVPQMKEPIEDLSPDRVLDLQADARLHVIFGGTKVVQHIPPQKATSGL 400
401 KPVDNGCVAFVLRTGFNTSQGRLLRTILFGVKRVTANNLETFIFILFLLV 450
451 FAIAAAAYVWVEGTKDPSRNRYKLFLECTLILTSVVPPELPIELSLAVNT 500
501 SLIALAKLYMYCTEPFRIPFAGKVEVCCFDKTGTLTSDSLVVRGVAGLRD 550
551 GKEVTPVSSIPIETHRALASCHSLMQLDDGTLVGDPLEKAMLTAVDWTLT 600
601 KDEKVFPRSIKTQGLKIHQRFHFASALKRMSVLASYEKLGSTDLCYIAAV 650
651 KGAPETLHSMFSQCPPDYHHIHTEISREGARVLALGYKELGHLTHQQARE 700
701 IKREALECSLKFVGFIVVSCPLKADSKAVIREIQNASHRVVMITGDNPLT 750
751 ACHVAQELHFIDKAHTLILHPPSEKGQPCEWRSIDSSIVLPLTLGSPKAL 800
801 ALEHALCLTGDGLAHLQAVDPQQLLCLIPHVQVFARVAPKQKEFVITSLK 850
851 ELGYVTLMCGDGTNDVGALKHADVGVALLANAPERVVERRRRPRDSPVLS 900
901 NSGPRVSRSTKQKSALLSPEEPPASHRDRLSQVLRDLEEESTPIVKLGDA 950
951 SIAAPFTSKLSSIQCICHVIKQGRCTLVTTLQMFKILALNALILAYSQSV 1000
1001 LYLEGVKFSDFQATLQGLLLAGCFLFISRSKPLKTLSRERPLPNIFNLYT 1050
1051 ILTVMLQFSVHFLSLVYLYREAQARSPEKQEQFVDLYKEFEPSLVNSTVY 1100
1101 IMAMAMQMATFAINYKGPPFMESLPENKPLVWSLAVSLLAIIGLLLGSSP 1150
1151 DFNSQFGLVDIPVEFKLVIGQVLALDFCLALLADRVLQFFLGTPKLRVPS 1200
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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