 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8UVK2 from www.uniprot.org...
The NucPred score for your sequence is 0.93 (see score help below)
1 MSDFIESEAEESEEEFEEKDLKPKKTQRFMEEDEEEEEENTEDQDEHGNL 50
51 RGLIDDDDVEEEEEEERGEPPAGEDSDSGEEVRHRRRKRSFDDYLDDDDL 100
101 DLIEENLGVKVKRRKKKYSRVKTMDDEGDDDDEKDLIADEIFTGDGDGEG 150
151 EVEDGEAVDTLHPRDDEEEEDDEESDIDDFIVDDDGQPITKKKGKKFSGY 200
201 TDAALQEAQEIFGGDFDFAEFDTEAYDHAEEEEEDQDDESWDRPKKQTKR 250
251 RVSRRSIFEIYEPSELESSHMTDQDNEIRSTDMPERFQLRAIPVKPAEDD 300
301 ELEEEAEWIYRNAFSTPTISMQESTDYLDRGTTTNFSRKGPSTIAKIKEA 350
351 LNFMRNQHFEVPFIAFYRKEYVEPELNINDLWKVWQWDEKWTQLKTRKQN 400
401 LTRLFQRMQSYQFEQISADPDKPLADSTRPLDTADMERLKDVQSIDELGD 450
451 VYNHFLLYYGRDIPKMQNAAKGGKKKLKKIKEVSEEDGEEAEVEEEEEEE 500
501 EQKGPDLKQASRRDMYSICQSAGLDGLAKKFGLTPEQFGENLRDSYQRHE 550
551 TEQFPAEPLELAKDYVCSQFNTPEAVLEGARYMVAMQIAREPLVRHVLRQ 600
601 TFQERAKINIKPTKKGKKDVDEAHFAYSFKYLKNKPVKELSGDQFLKMCL 650
651 AEEEGLLAIDICIDLVGVKGYGDQTYFDEIKQFYYRDEFSHQVQEWNKQR 700
701 TLAIERSLQQFLYPQMAKELKNKLIAEAKDNIVKSCCKKLYNWLKVAPYR 750
751 PDQQVEEDDDLMDESQGKGIRVLGVAFASGRDTPVFCSLINGEGEVVDFL 800
801 RLPYFLKRRNAWREDEREKKQQDVENLKKFLLSKKPHVVAVSGENRDAHM 850
851 VMEDIKRTISELEQNSSLPVVGVELVDNELAVLYMNSKKSEADFRDYPPL 900
901 LRQAVSVARKIQDPLVEFAQVCSTDDDILCLKLHPLQEHVVKEELLSALY 950
951 CEFINRVNEVGVDVNRAIAHPYTQSLVQYICGLGPRKGSHLLKILKQNNT 1000
1001 RLENRTQLVTMCHMGPKVFINCAGFIKIDTASLGDSTDSYIEVLDGSRVH 1050
1051 PETYEWARKMAVDALEYDESAEDANPAGALEEILENPERLKDLDLDAFAE 1100
1101 ELERQGYGNKGITLYDIRAELSCRYKDLRAPYRPPNTEEVFNMLTKETPE 1150
1151 TFYIGKLITCVVTNIAHRRPQGESYDQAIRNDETGLWQCPFCQQDNFPEL 1200
1201 SEVWNHFDSGSCPGQAIGVRTRLDNAVMGFIPTKFLSDKVVKHPEERVKP 1250
1251 GMTVHCRIMKIDIEKFNVDLTCRTSDLSDKNNEWKLPKDTYYDFDAETDD 1300
1301 VKQEEEQKKKQQRTTYIKRVIAHPSFHNINFKQAEKMMESMDQGDVVIRP 1350
1351 SSKGENHLTVTWKVADGIYQHVDVREEGKENAFSLGHTLWINTEEFEDLD 1400
1401 EITARYVQPMAAFARDLLGHKYFHECNGGDRKKMEELLVRTKKEKPTFIP 1450
1451 YYISACRDLPGKFLLGYQPRGKPRIEYVTITPDGFRYRSQIFPTVNGLFR 1500
1501 WFKDHYQDPVPGVTPASSRTRTPASVNATPANINIADLTRAVNSLPRNMT 1550
1551 SQMFNAIAAVTGQGQNPNTTPAQWASSQYGYSGGSSAGGGGGSSSAYHVF 1600
1601 ATPQQPMATPLMTPSYSYTTPGQQQAMTTPQYPSSTPQSSHGHHQHSSST 1650
1651 PSSSSSRVRTPQPKASSHTAVDWGKMAEQWLQEKEAERRKQKTPRMTPRP 1700
1701 SPSPMIESTPMSIAGDATPLLDEMDR 1726
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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