 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q2PC93 from www.uniprot.org...
The NucPred score for your sequence is 0.68 (see score help below)
1 MGIVATVLLWVVTEAARGRWCERTEQVTEEEVVMPRREDVVPCPSMYQYS 50
51 LAGWRIDLNRMRQVYGGERGVPPTSTHPGAAMCYIYRPPETQLVVRNRTV 100
101 RACCAGWSGPHCTEVEGSLGQCHASWQCQDALGAHNLSTVSMAECCRQPW 150
151 GHSWRNGSSALCFACSRQPLTGDVPLPTAPRGPAARHRGPTASCTVWAGS 200
201 RYRSFDGRHFGFQGECAYSLAASTDSTWAVSITPGSPPVLHMTFGLDTVV 250
251 AQGHNISVNGVAVPEGRQHLHGGISVTWLGDFVAVESGLGVHLKLDGRGT 300
301 VYVTVSAELRGSTKGLCGPYNDDPIDDFLRVEGDVAPLAASFGNSWRIPD 350
351 ANPELSCSDAVEPSPGCAMGSTAQRAAEAMCGMLLTDPFRQCHEAVDPHG 400
401 FYEACLELHCREGGTGPSPPPAVCDTLATYVRDCAQRRAYIEWRRPGLCE 450
451 QQCGHGQRYSDCVSSCPASCMAAGTAEEGHCRDDCASGCECTPGLLLDRG 500
501 ACIPQSACPCLHRGHIYAPGQSIRQRCNQCTCRGGRWLCTQDRCAAECAV 550
551 LGDLHYITFDRRRFSFPGACEYTLVQDFVEGTLRITAEQEACGGHQPLSC 600
601 LRALSITVPGASARLHSTGEVVVDGRVVPLPFASAALTVRRASSSFLLLQ 650
651 TFGAHLLWGLETPAAYITLQPAFANKVRGLCGTYNWDQRDDFATPAGDVE 700
701 VGVTAFANKYRVSTDCPVLSPVPFEPCSTYAPRRELAAAACAILHGASFQ 750
751 PCHHLVDREPFHQLCLYDVCACPAGKHCLCPALAAYARECAQEGAALSWR 800
801 NESFCGTQCRGGQVYQECSSPCGRTCADLRLDGASSCPSLDNICVSGCNC 850
851 PEGPVLDDGGQCVPPGVCPCQHSSQLYPAGSKIRQGCNACMCTAGTWSCT 900
901 DAPCPDAAFCPGDLVYVFGSCLRTCDSAEPNGTCTGIADGCVCPPGTVFL 950
951 DERCVPPEECPCQHNGRLYHPNDTIVRDCNTCVCRQQRWQCSSEDCMGTC 1000
1001 VATGDPHYITFDGRAFSFLGDCEYVLVREANGLFTVTAENVPCGTSGVTC 1050
1051 TKSVVVEMGNTVVHMLRGRDVTVNGVSVRPPKVYSGNGLTLQRAGIFLLL 1100
1101 LSRLGLAVLWDGGTRVYIRLQPQHRGRVVGLCGNFDRDAENDLASQQGVL 1150
1151 EPTAELFGNSWRVSLLCPEVDGTTAQHPCTDNPHRATWARKRCSILTQRL 1200
1201 FAPCHDEVPCQHFYDWCIFDACGCDSGGDCECLCTAIATYAEECSQRGIH 1250
1251 IRWRSQDLCPMQCDGGQEYSACGPPCPQTCRNLGLELPEHCDTMSCLEGC 1300
1301 FCPEGKVLHEGSCIDPAECPCFWQGIAFPDSAVVQQGCRNCSCTAGLWQC 1350
1351 VPTAEPCPAQPHCPDSEFPCRSGGRCVPGAWLCDNEDDCGDGSDEVCALH 1400
1401 CAPHQHRCADGQCVPWGARCDGLSDCGDGSDERGCPPPPCAPPEFRCASG 1450
1451 RCIPRAHVCNGELDCGFADDSDEAGCSPSCSVGEFQCAAGRCVPYPHRCN 1500
1501 GHDDCGDFSDERGCVCPAGHFQCPDAQCLPPAALCDGMQDCGDGTDEAFC 1550
1551 PDRITCAPGQLPCPDGSCVSQVKLCDGIWDCRDGWDESSVRCMVSWAPPA 1600
1601 PTQLPTVPANGTAAPVCGPYEFPCRSGQCVPRGWVCDSEADCPDNSDELG 1650
1651 CNRSCVLGHFPCALGAHCIHYDHLCDGIPHCPDHSDESDDNCGSTQIPPC 1700
1701 PGHFVCNNRVCVNATRVCDGALDCPQGEDELACEGYVPTGERNQTVGPCA 1750
1751 EYSCRDGDCITFKQVCNGLPDCRDGDMASGWLPSDEWDCGQWGPWAPWGI 1800
1801 CSHSCGLGQQLRARECSQRTPGVLHQCHGEATQARPCFSTACPVDGAWSE 1850
1851 WTMWSNCTQGCEGVVVRQRHCQPPRDGGRPCAALPATAHATLEIGTCQQD 1900
1901 GCPPASCPGGLQPRPCAPCPASCADLASRAPCRREQCTPGCWCAEGLVLD 1950
1951 GERGCVRPRECRCEVDGLRYWPGQRMKLNCRLCTCLDGQPRRCRHNPACS 2000
2001 VSCSWSAWSPWGECLGPCGVQSIQWSFRSPSHPGKHGTNRQCRGIYRKAR 2050
2051 RCQTEPCQECEHQGRSRAQGDRWRWGPCHVCQCLPGPEVRCSPYCARSAV 2100
2101 GCPQGQVLVEGKGDSCCFCAQIGDNVTAIPTALTMEPPSTMPGEPSDSPL 2150
2151 PTFPLPSPGDPCYSPLGIASLPDSSFTASAEQQQHPARAARLHHVSPGLE 2200
2201 LQGWAPPADTVPGLPSHLPFLQLDLLQTTNLTGVVVQGAGAGDAFITAFQ 2250
2251 LQFSTDGNRWHNYQQLFQGNWDATTPVVQPLDHMVQARYIRILPQGFHNA 2300
2301 IFLRAELLGCPTVPLDLAVTTAVTPAPCGTGEFWCGVSCVTASRRCDGAT 2350
2351 DCPGGADEAGCEPPSSTTLPTHPASLTTPGSAGILGLTAEPPVAPPAAVP 2400
2401 EGTSAWLTVGSTSPAVPSTTGLPGVPTATITPRGPPSAGPPSPGMAAVTV 2450
2451 SHPVMGPPALPMPPTGVPTPTSAEPPLPRLLCPPDQFLCDALGCVDAAMV 2500
2501 CDGQQDCLDGSDEAHCGALPTSGSSPSPLAWPSSPPPTCSPKQFSCGTGE 2550
2551 CLALEKRCDLSRDCADGSDESSCADCILSPWGGWSQCSHSCGLGVTSRQR 2600
2601 VLLRGALPGGTCHTPRLDTRACFLRACPVPGAWAAWGVWSSCDAECGGGM 2650
2651 RSRTRSCTDPPPKNGGQPCAGEALQSQPCNLQPCGDTRECGPGMVLVQEG 2700
2701 DCVQGLVPPCPQVCGDLSATSSCQSPCQEGCRCPPGLFLQEGTCVNASQC 2750
2751 HCHQGQQRWLPSQVFLRDGCSQCVCRDGVVTCEDTACPIACAWSAWSLWT 2800
2801 LCDRSCGVGMQERFRSPSNPAAANGGAPCDGDTREVRECHTPCATAEPSS 2850
2851 GWSSWTPWSPCSRSCFHHVDQRGRRHRFRHCEGMGTCPGLGVQEEPCDTA 2900
2901 PCPVAGVWMPWSAWSECSAPCDAGVQTRSRTCTPPAFGGAECTGPHLQTR 2950
2951 NCNTRPCGAQCPDTMQYLTAEECRHSEGRCPWICQDLGAGVACTAQCQPG 3000
3001 CHCPAGLLLQNGTCVPPSHCLCHHRGHLYQPGDINALDTCNNCTCVTGQM 3050
3051 VCSTETCPVPCTWSNWTAWSTCSHSCDVGMRRRYRVPIVPPLAGGGPPCQ 3100
3101 GPSMEVEFCSLQPCRAVAPWGPWSECSVSCGGGYRNRTRDGPPLHSLEFS 3150
3151 TCNPAPCPGKEPGVCPPGKQWQACAQGAASCAELSAAPPADGSCHPGCYC 3200
3201 PPGALLLNNECVAEAACPCAVDGVLYQPGDVVPQGCHNCSCIAGRVTNCS 3250
3251 QEDCGDVDGPWTPWTPWSECSASCGPGRQRRYRFCSAHPGVPCAEPQPQE 3300
3301 RPCARQPCHSPDCAAVPGSVFSHCRPPCPRSCDDISHCVWHRQPGCYCTN 3350
3351 GTLLDATGTACVALENCTCLDAHSGQRHQPGQSVPRGDGCNNCTCTQGRL 3400
3401 LCTGLPCPVPGAWCEWSPWTPCSRSCGDEAATRHRVCSCPAPQQGGAGCP 3450
3451 GGLEGHGDTGMQLQHQECPSVPPCPEDGAWAAWGPWSGCGGCGGQAVRTR 3500
3501 SCSSPPARFGGLPCAGEARQSRACPWATSSCPECAGGLVAFTCGKPCPHS 3550
3551 CEDLREDTACMATPRCLPACACPHGQLLQDGDCVPPELCRCAWAPSKNGS 3600
3601 IWEQDGAVPMQELQPGETVQRHCQNCTCKSGTLQCHAEPGCRADGGWSPW 3650
3651 GPWSPCSPGCQAGTQLASRQCNNPTPQLGGRGCSGHSQRQRPCPATEGCP 3700
3701 EEEPWGEWSPWGPCSASCGGGEQLRHRDCPPPGGCPGLALQSKTCNTHVC 3750
3751 REAGCPPGRLYRECQQGEGCPYSCAHLAGRIACFPGGCQEGCHCPTGTLL 3800
3801 HHGHCLQECPCVLTAEVLRKLRNSSADLQAAPHLLGTRGPPLALDQELPP 3850
3851 GSTIHSACTSCTCLHGRLNCSEPVCPRDGGFSPWGPWSSCSRSCGGLGVM 3900
3901 TRRRGCTNPEPARGGRDCAGPRSDSKYCQSPECPAVPTTEPGPGVAGAEE 3950
3951 EEGFGPWSPWSPCSKTCTHPERPATKTRERPCVGTAVCSGDGFQEQPCNL 4000
4001 PLCSDVPPCQGEDCAGLNCSWAPWGPWTECSRSCGVGRQQRLRAYSPPGA 4050
4051 SGRWCPGILSAFVQRRFCSLQACKVDGAWSAWSPWSRCDRTCGGGRAVRT 4100
4101 RSCTRPPPKNGGQRCPGERHQLHLCNAQPCDDSCPPGMALVTCANHCPRH 4150
4151 CGDLQEGIVCREEEHCEPGCRCPNGTLEQDGGCVPLAHCECTDAQGHGWV 4200
4201 PGSTHHDGCNNCTCLEGRLRCTDRLCPPLRCPWSRWSRWSPCSVTCGDGQ 4250
4251 QTRFRTPTAGSWDEECQGEQMENRGCAAGPCPPLCPQGSWERRLGDMWLQ 4300
4301 GECQRCTCTPEGTVCEDTTCAGAEHCTWGTWSPCSRSCGTGLASREGSCP 4350
4351 CPFPGPPGAVCNASTGDGARPHREVQACYLRPCPAECSWSAWSSWGGCSC 4400
4401 SSPLQHRYRHRHGTGLCVGLDVELHPCNTSGCSESSCEPPFEFQPCSPPC 4450
4451 ARLCSTLQHPELCPAQSHCLPGCFCPQGLLEQRSACVPPEQCDCLHTNES 4500
4501 GDLVTLSPGDIILLGCKECVCQDGALQCSSEGCQGLLPLSPWSEWTPCST 4550
4551 CLPLFPSHLGDATPHVSVQHRYRACLDPQSGQPWSGDTAVCSAELQQQRL 4600
4601 CPDPDICQELCLWSPWGPWGPCQQPCSGSFRLRHRHLQRLAGSGQCQGAQ 4650
4651 TQSESCNTAVCPGEDCEKQGRVFATTCANSCPRACADLWQHVECVQGGCK 4700
4701 PGCRCPQGQLLQDGLCVPTAQCRCGLSGDNGTQELWPGQEATIECHNCTC 4750
4751 ENGTMVCPALPCPSYGPWSTWSPCSSSCGSGRTSRHRTCEPNPGGVPCMA 4800
4801 SGMQETAECSPQPCPAGCQLSPWSPWSPCSSSCGGGRSERSRELLGGEEE 4850
4851 PCPIPALRQHRVCNVHNCTQECPRSQVHRECANACPHACADLRPQTQCLP 4900
4901 QPCQPGCACPPGQVLQDGACVPPEECRCTLDSTMPGVLNLSREEQEQEHA 4950
4951 PGSRLQHRCNTCICIRGTFNCSQEECNVDCLWSPWSPWSPCSVTCGMGER 5000
5001 LSHRHPLRQRLYEGAECLGPPVRRAACHLPDCACPEGERWQGHEVPPGCE 5050
5051 QSCRDILDETPANCTPSPSPGCTCEPGHYRNSSGHCVPSTLCECLHQGQL 5100
5101 HQPGSEWQEQCARCRCVDGKANCTDGCTPLSCPEGEVKVREPGRCCPVCR 5150
5151 MEWPEEPSSMCRRFTELRNITKGPCSLPNVEVSFCSGRCPSRTAVTPEEP 5200
5201 YLQTLCECCSYRLDPGSPVRILSLPCAGGAAEPVVLPIIHSCECSSCQGG 5250
5251 DFSKR 5255
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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