 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q6A009 from www.uniprot.org...
The NucPred score for your sequence is 0.79 (see score help below)
1 MGGKNKQRTKGNLRPSNSGRAAELLAKEQGTVPGFIGFGTSHSDLGYVPA 50
51 VQGAEDIDSLVDSDFRMVLRKLSKKDVTTKLKAMQEFGIMCTERDTEAVK 100
101 GVLPYWPRIFCKISLDHDRRVREATQQAFEKLILKVKKHLAPYLKSVMGY 150
151 WLMAQCDTYPPAALAAKDAFEAAFPPSKQPEAIAFCKEEITTVLQDHLLK 200
201 ETPDTLSDPQTVPEEEREAKFHRVVTCSLLALKRLLCFLPNNELDSLEEK 250
251 FKSLLSQNKFWKYGKHSVPQVRSAYFELVSALCQHVPQVMKEEAAKVSPS 300
301 VLLSIDDSDPVVCPALWEAVLYTLTTIEDCWFHVNAKKSVFPKLMAMIRE 350
351 GGRGLAAVMYPYLLPFISKLPQSITEPKLDFFKNFLTSLVTGLSTERTKS 400
401 SSSECSAVISAFFECLRFIMQQNLGEEEMVQMLINEQLIPFIDTVLKDSG 450
451 LHHGPMFDHLADTLSSWEAKADAERDPGAVYNLENVLLSFWGRLSEICTE 500
501 KIRQPEADVKSVLCVSSLVGVLQRPRSSLKLHRKKTAQVRFAINIPEAHK 550
551 GDEKSMSSEGENSEGSDGGAQSPLSNTSSDLVSPLRKKPLEDLVCKLAEV 600
601 SISFVNERKSEQHLQFLSTLLDSFSSVQVFNILLSDKQKNVVKAKPLEIT 650
651 KLAEKNPAVKFLYHKLIGWLNDSQKEDGGFLVDILYSALRCCDSGVERKE 700
701 VLDDLTKEDLKWSSLLQVIEKACSSSDKHALVTPWLKGSILGEKLVALAD 750
751 CLCDKDLEATTSESHSSEQWSLLRLALSQHVKNDYLIGEVYVGRIIVKLH 800
801 ETLSKTKDLSEAANSDSSVSFVCDVVHSFFSSAGGGLLMPPSEDLLLTLF 850
851 QLCAQSKERTHLPDFLICKLKNTLLSGVNLLVHQTASTYEQSTFLRLSVL 900
901 WLKDQVQSSALDNTSLQVLLSAAGDLLGTLVESEDTSLLGVYIGSVMPSD 950
951 SEWEKMRQALPVQWLHRPLLEGRLSLNYECFKTDFKEQDTKTLPNHLCTS 1000
1001 SLLSKMILVAQKKKLVLEDNVLEKIIAELLYSLQWCEELDNAPSFLSGFC 1050
1051 GILQKMNITYSNLSVLSETSSLLQLLFDRSRKNGTLWSLIIAKLILSRSI 1100
1101 SSDEVKPYYKRKESFFPLTEGSLHTIQSLCPFLSKEEKKEFSAQCIPAFL 1150
1151 GWTKEDLCSINGAFGHLAIFNSCLQTRSIDDKQLLHGILKIITSWRKQHE 1200
1201 DIFLFSCNLSEASPEVLGLNIEIMRFLSLFLKHCAYPLPLADSEWDFIMC 1250
1251 SMLAWLETTSENQALYSVPLVQLFACVSFDLACDLCAFFDSITPDIVDNL 1300
1301 PVNLISEWKEFFSKGIHSLLLPLLVNAIGENKDLSETSFQNAMLKPMCET 1350
1351 LTYISKDQLLSHKLPARLVASQKTNLPEHLQTLLNTLTPLLLFRARPVQI 1400
1401 AAYHMLCKLMPELPQHDQDNLRSYGDEEEEPALSPPAALMSLLSSQEELL 1450
1451 ENVLGCVPVGQIVTVKPLSEDFCYVLGYLLTWKLILTFFKAASSQLRALY 1500
1501 SMYLRKTKSLNKLLYHLFRLMPENPTYGETAIEVSSKDPKTFFTEEVQLS 1550
1551 IRETATLPYHIPHLACSVYHMTLKDLPAMVRLWWNSSEKRVFNIVDRFTS 1600
1601 KYVSNVLSFQEISSVQTSTQLFNGMTVKARATTREVMATYTIEDIVIELI 1650
1651 IQLPSNYPLGSITVESGKRIGVAVQQWRNWMLQLSTYLTHQNGSIMEGLA 1700
1701 LWKNNVDKRFEGVEDCMICFSVIHGFNYSLPKKACRTCKKKFHSACLYKW 1750
1751 FTSSNKSTCPLCRETFF 1767
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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