 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9VDW6 from www.uniprot.org...
The NucPred score for your sequence is 0.97 (see score help below)
1 MEPGILIDERQHIQKKTFTKWINSHLIDTQCTPVKDLFLDLRDGHRLLAL 50
51 LSTLTQTNLKPEKGRMRVHHINNLNKVITEIQQHGVKLVNISSDDIVGGN 100
101 AKLTLGLIWLIALEFNGQHLVKSHSSNGVEKSLLAWARQYTEPHGLQLND 150
151 FSSSWSDGRAFLMILDAHVEELNLQAALQQHALKRLHLAFDLAHRHFKIE 200
201 KLLDAEDVHTHKPDNKSIQMYVMCLYHAMESMRTRQQEQEQDEGQDQDPG 250
251 RVPCTSITDLDEVPLDNDQTSLGLYTSDSAGSMEQRSSGELKTHSMRPLS 300
301 TATNASVEISGYQSALEAVLTLLLEDEQLLSQNLPDPQDFQTAKLQFHEN 350
351 ESFMLKLTEHQEYVGEALEEGSNLINESQKAGAGLSQEDQNEVRQQMVLL 400
401 NERWETLRLRALDVQAKILMRLAEFQKQKLEQLRQFLTSVEDRISHMSDI 450
451 GPTLEEAEKQLLEAQKLKADLSEQQELVDSLSSMVVIVNDTSGNFNDLED 500
501 RLSALGERWSHVVKWSDLRKEKLQQYKCISRWLDAREQDLKLMESRDVTD 550
551 VGGITQRINELNYCAKDLLELQRYLIDLRQMVAATLQDGDDKGERVLIQL 600
601 ESYEDRLDALKQIVEVQTVRIETKGFNFGRDRASYDDSRVVRPEGWVDYQ 650
651 MIIRFGEDDSQEDDDEHDLASKKRKLRNADNFNALENHIMEHFGYVQEVE 700
701 QKLQQLQRQSLRQQCELLKELQAENSRRCGTLPELKKLYEVCELEDPSRN 750
751 LLLEETHIKQLEQRYANLSQKLSSQQSESHTLLAKEKYYNSLTGFKLVLA 800
801 DSRDWYKQHAGSASGNELEQRLSHMESLASEISEAKTATEELDDNLIEWK 850
851 QDFGLFYDSWHDMKQALQALIQQRGGESLSRQLKQIQDFVTKVSNQKVRV 900
901 SNLEVMQEQQHFLNQLLDEMESLRLTYDNIPKHLIGEELQTAWNRLPEQL 950
951 NERVIKQTTAIENLNHFAAEYNAIIAMLRSAADSKLNGSDGASSQDLRKL 1000
1001 EIDVISARNFSEILIKEAEPAQKESLQSQIRALNTLYDQVEQVHREKKEQ 1050
1051 QTVLQSHIDLIQLRLKETDQWLTDLESNTPKSGISDIVNSNELFQSKSRF 1100
1101 QTLKETCERETTQFRDLNERGGELLLQMDELQDQDRESRYGSLAKQFTRI 1150
1151 NARWTEVTELVYAKTALLEHISTQLGEFKKFMVSETGYLDKLENKIRNTP 1200
1201 ENAADAEEIMEELDDLENVLRSHSEEWLDKIQEIGNELIDNEFMADSIRR 1250
1251 DIDETVQRWTQLQQQAKKRTELLEQKVSEAEQSEKCIVQFEKWLTRVDDI 1300
1301 LSDHLDNDVTIVDQPEEFQRLAHEFVANEKNFKEISELIDEHTRNGKVGA 1350
1351 ANRLQEQLNLMEVRFKYCQAKLSKCTAIQHSYESRLNRAYTDLRNVERST 1400
1401 EVVDVASAGPNTVQTQYQKCLQIYRTLSEIKSEIESTIKTGRRVCEDRYT 1450
1451 KSPKQLSQRIDALKHLYNTLGENVTQSKATLERLLTLARQLEECFDSADN 1500
1501 LIRRFESPQEVHDRNSILLEFEDVLRRCEDHYNEYNKSCDQSCMVETRQR 1550
1551 IDGLKATYHKLTSADIIKRLTEMKTTLQNLDNISLETLRAMEHDLKEINV 1600
1601 PSNPEIEKLQQQVIAIVVDVLKTRFNEATTLAARNTSSPDNDDTEIVVVS 1650
1651 DTVRQRRARTPQSGESPSSAHTSSSESPTKGVENSPGAVGDQVMPDLLPP 1700
1701 QTFRLAESSTLFSQISLNPQKVTNTPPPKPAKTKRKAPSSPAQVVEIRVK 1750
1751 NIQNDKMSVQNIDLEPQQGEIVDTVNILESVEPFVPEYVETVQIVDLSED 1800
1801 SDSSVRVDSQGKEMRRSKSKHSLNETPLPKVSDNDEDSAEQEEDLLRPSA 1850
1851 ENTSTPFLRVEKRRISFDEKRKRVANERDILRDSEEEEPKTPDTPRAAQV 1900
1901 SKPKRWRQLQPEMDALEPESPGRDSFYSPDKESGFDAEPLVFSDDEDIPR 1950
1951 FSLEMTSTIDSDSDTSRIMTPSTKNPNPFLSKVLESLSSPVDDSNVTLKS 2000
2001 PISEEQPQNLDDRVREFDKQAKQMIYKLKLTKAKIEQCHESEAEDLRLLI 2050
2051 APDAATLISQGDSLVLETHGRQGSISRLVMRTQIILREQFREVQQARSKT 2100
2101 SGSGAPAPPLDSVNIEELVTKGLRRINVLIEKTVDLKSSTDLEKRMEDIN 2150
2151 ERHDDLQVIVSAIGKNAQMPKVTPLMMNEIEKTKNNLIAHADSIELSLTE 2200
2201 LRNGPRISNGKERPDASSAATMSCRSEYNNEPSGTGALAGSFDKSVLQIS 2250
2251 DWLTWEQNMIKIQSVLVDDGDAVRLAIEKQEKVLRELKMKKPQLNELVHT 2300
2301 AEVLKGDVKRQQLQEKELKQFSLAPHCSADLDYMRCCLKVTRLREHWDET 2350
2351 SQCVLQRAAQLKNMLSDSQRFEAKRLELEKWLARMEQRAERMGTIATTAD 2400
2401 ILEAQQKEQKSFHAELHQNKQHFDIFNELTQKLIAVYPNDDTTRIKKMTE 2450
2451 VINQRYANLNSGVINRGKQLHAAVHSLQSFDRAMDQFLAFLSETETLCEN 2500
2501 AESDIERNPLMFKDLQSEIETHRVVYDRLDGTGRKLLGSLTSQEDAVMLQ 2550
2551 RRLDEMNQRWNNLKSKSIAIRNRLESNSEHWNALLLSLRELTEWVIRKDT 2600
2601 ELSTLGLGPVRGDAVSLQKQLDDHKAFRRQLEDKRPIVESNLTSGRQYIA 2650
2651 NEAAVSDTSDTEANHDSDSRYMSAEEQSRELTRSIRREVGKLSEQWNNLI 2700
2701 DRSDNWKHRLDEYMTKMRQFQKILEDLSSRVALAEQTKTSWLPPSSVGEA 2750
2751 NEQMQQLQRLRDKMTTASALLDDCNEQQSFFTANQVLVPTPCLSKLEDLN 2800
2801 TRMKLLQIAMDERQKVLCQAGAQQTHENGDDGRTTSNSGTIGPLPNLGQS 2850
2851 VKPPWERATTAANVPYYIDHERETTHWDHPEMIELMKGLADLNEIRFSAY 2900
2901 RTAMKLRSVQKRLALDRISMSTACESFDRHGLRAQNDKLIDIPDMTTVLH 2950
2951 SLYVTIDKIDLTLMLDLAINWILNVYDSQRTGQIRVLSFKVGLVLLCKGH 3000
3001 LEEKYRYLFRLVADTDRRADQRRLGLLLHDCIQVPRQLGEVAAFGGSNIE 3050
3051 PSVRSCLEQAGISQEAIDGNQDISIELQHFLGWLQHEPQSLVWLPVLHRL 3100
3101 AAAEAAKHQAKCNICKEYPIVGFRYRCLKCFNFDMCQKCFFFGRNAKNHK 3150
3151 LTHPMHEYCTTTTSTEDVRDFTRALKNKFKSRKYFKKHPRVGYLPVQSVL 3200
3201 EGDALESPAPSPQHTTHQLQNDMHSRLEMYASRLAQVEYGGTGSNSTPDS 3250
3251 DDEHQLIAQYCQALPGTSNGSAPKSPVQVMAAMDAEQREELEAIIRDLEE 3300
3301 ENANLQAEYQQLCSKEQSGMPEDSNGMQHSSSSMTGLSGQGEQGQDMMAE 3350
3351 AKLLRQHKGRLEARMQILEDHNRQLEAQLQRLRQLLDEPNGGGSSATSSG 3400
3401 LPSAPGSALNSKPNTLQTRSVTASQLNTDSPAKMNQQNGHYEHNSKGIML 3450
3451 PGMNSEIQQQHAQLASLAAKHHQHQLSGALNALHQQQQQQLQQQPPQQQR 3500
3501 SMMTGNGGMDISGGMQTSGGYLGDDGRPPPPPHSSLMQQQHQQHLNENSS 3550
3551 GLVTVITEQELESINDDLEDSSSSNTTNTTTTTTTTATTEKTCVELQK 3598
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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