 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8NEZ4 from www.uniprot.org...
The NucPred score for your sequence is 0.98 (see score help below)
1 MSSEEDKSVEQPQPPPPPPEEPGAPAPSPAAADKRPRGRPRKDGASPFQR 50
51 ARKKPRSRGKTAVEDEDSMDGLETTETETIVETEIKEQSAEEDAEAEVDN 100
101 SKQLIPTLQRSVSEESANSLVSVGVEAKISEQLCAFCYCGEKSSLGQGDL 150
151 KQFRITPGFILPWRNQPSNKKDIDDNSNGTYEKMQNSAPRKQRGQRKERS 200
201 PQQNIVSCVSVSTQTASDDQAGKLWDELSLVGLPDAIDIQALFDSTGTCW 250
251 AHHRCVEWSLGVCQMEEPLLVNVDKAVVSGSTERCAFCKHLGATIKCCEE 300
301 KCTQMYHYPCAAGAGTFQDFSHIFLLCPEHIDQAPERSKEDANCAVCDSP 350
351 GDLLDQFFCTTCGQHYHGMCLDIAVTPLKRAGWQCPECKVCQNCKQSGED 400
401 SKMLVCDTCDKGYHTFCLQPVMKSVPTNGWKCKNCRICIECGTRSSSQWH 450
451 HNCLICDNCYQQQDNLCPFCGKCYHPELQKDMLHCNMCKRWVHLECDKPT 500
501 DHELDTQLKEEYICMYCKHLGAEMDRLQPGEEVEIAELTTDYNNEMEVEG 550
551 PEDQMVFSEQAANKDVNGQESTPGIVPDAVQVHTEEQQKSHPSESLDTDS 600
601 LLIAVSSQHTVNTELEKQISNEVDSEDLKMSSEVKHICGEDQIEDKMEVT 650
651 ENIEVVTHQITVQQEQLQLLEEPETVVSREESRPPKLVMESVTLPLETLV 700
701 SPHEESISLCPEEQLVIERLQGEKEQKENSELSTGLMDSEMTPTIEGCVK 750
751 DVSYQGGKSIKLSSETESSFSSSADISKADVSSSPTPSSDLPSHDMLHNY 800
801 PSALSSSAGNIMPTTYISVTPKIGMGKPAITKRKFSPGRPRSKQGAWSTH 850
851 NTVSPPSWSPDISEGREIFKPRQLPGSAIWSIKVGRGSGFPGKRRPRGAG 900
901 LSGRGGRGRSKLKSGIGAVVLPGVSTADISSNKDDEENSMHNTVVLFSSS 950
951 DKFTLNQDMCVVCGSFGQGAEGRLLACSQCGQCYHPYCVSIKITKVVLSK 1000
1001 GWRCLECTVCEACGKATDPGRLLLCDDCDISYHTYCLDPPLQTVPKGGWK 1050
1051 CKWCVWCRHCGATSAGLRCEWQNNYTQCAPCASLSSCPVCYRNYREEDLI 1100
1101 LQCRQCDRWMHAVCQNLNTEEEVENVADIGFDCSMCRPYMPASNVPSSDC 1150
1151 CESSLVAQIVTKVKELDPPKTYTQDGVCLTESGMTQLQSLTVTVPRRKRS 1200
1201 KPKLKLKIINQNSVAVLQTPPDIQSEHSRDGEMDDSREGELMDCDGKSES 1250
1251 SPEREAVDDETKGVEGTDGVKKRKRKPYRPGIGGFMVRQRSRTGQGKTKR 1300
1301 SVIRKDSSGSISEQLPCRDDGWSEQLPDTLVDESVSVTESTEKIKKRYRK 1350
1351 RKNKLEETFPAYLQEAFFGKDLLDTSRQSKISLDNLSEDGAQLLYKTNMN 1400
1401 TGFLDPSLDPLLSSSSAPTKSGTHGPADDPLADISEVLNTDDDILGIISD 1450
1451 DLAKSVDHSDIGPVTDDPSSLPQPNVNQSSRPLSEEQLDGILSPELDKMV 1500
1501 TDGAILGKLYKIPELGGKDVEDLFTAVLSPANTQPTPLPQPPPPTQLLPI 1550
1551 HNQDAFSRMPLMNGLIGSSPHLPHNSLPPGSGLGTFSAIAQSSYPDARDK 1600
1601 NSAFNPMASDPNNSWTSSAPTVEGENDTMSNAQRSTLKWEKEEALGEMAT 1650
1651 VAPVLYTNINFPNLKEEFPDWTTRVKQIAKLWRKASSQERAPYVQKARDN 1700
1701 RAALRINKVQMSNDSMKRQQQQDSIDPSSRIDSELFKDPLKQRESEHEQE 1750
1751 WKFRQQMRQKSKQQAKIEATQKLEQVKNEQQQQQQQQFGSQHLLVQSGSD 1800
1801 TPSSGIQSPLTPQPGNGNMSPAQSFHKELFTKQPPSTPTSTSSDDVFVKP 1850
1851 QAPPPPPAPSRIPIQDSLSQAQTSQPPSPQVFSPGSSNSRPPSPMDPYAK 1900
1901 MVGTPRPPPVGHSFSRRNSAAPVENCTPLSSVSRPLQMNETTANRPSPVR 1950
1951 DLCSSSTTNNDPYAKPPDTPRPVMTDQFPKSLGLSRSPVVSEQTAKGPIA 2000
2001 AGTSDHFTKPSPRADVFQRQRIPDSYARPLLTPAPLDSGPGPFKTPMQPP 2050
2051 PSSQDPYGSVSQASRRLSVDPYERPALTPRPIDNFSHNQSNDPYSQPPLT 2100
2101 PHPAVNESFAHPSRAFSQPGTISRPTSQDPYSQPPGTPRPVVDSYSQSSG 2150
2151 TARSNTDPYSQPPGTPRPTTVDPYSQQPQTPRPSTQTDLFVTPVTNQRHS 2200
2201 DPYAHPPGTPRPGISVPYSQPPATPRPRISEGFTRSSMTRPVLMPNQDPF 2250
2251 LQAAQNRGPALPGPLVRPPDTCSQTPRPPGPGLSDTFSRVSPSAARDPYD 2300
2301 QSPMTPRSQSDSFGTSQTAHDVADQPRPGSEGSFCASSNSPMHSQGQQFS 2350
2351 GVSQLPGPVPTSGVTDTQNTVNMAQADTEKLRQRQKLREIILQQQQQKKI 2400
2401 AGRQEKGSQDSPAVPHPGPLQHWQPENVNQAFTRPPPPYPGNIRSPVAPP 2450
2451 LGPRYAVFPKDQRGPYPPDVASMGMRPHGFRFGFPGGSHGTMPSQERFLV 2500
2501 PPQQIQGSGVSPQLRRSVSVDMPRPLNNSQMNNPVGLPQHFSPQSLPVQQ 2550
2551 HNILGQAYIELRHRAPDGRQRLPFSAPPGSVVEASSNLRHGNFIPRPDFP 2600
2601 GPRHTDPMRRPPQGLPNQLPVHPDLEQVPPSQQEQGHSVHSSSMVMRTLN 2650
2651 HPLGGEFSEAPLSTSVPSETTSDNLQITTQPSDGLEEKLDSDDPSVKELD 2700
2701 VKDLEGVEVKDLDDEDLENLNLDTEDGKVVELDTLDNLETNDPNLDDLLR 2750
2751 SGEFDIIAYTDPELDMGDKKSMFNEELDLPIDDKLDNQCVSVEPKKKEQE 2800
2801 NKTLVLSDKHSPQKKSTVTNEVKTEVLSPNSKVESKCETEKNDENKDNVD 2850
2851 TPCSQASAHSDLNDGEKTSLHPCDPDLFEKRTNRETAGPSANVIQASTQL 2900
2901 PAQDVINSCGITGSTPVLSSLLANEKSDNSDIRPSGSPPPPTLPASPSNH 2950
2951 VSSLPPFIAPPGRVLDNAMNSNVTVVSRVNHVFSQGVQVNPGLIPGQSTV 3000
3001 NHSLGTGKPATQTGPQTSQSGTSSMSGPQQLMIPQTLAQQNRERPLLLEE 3050
3051 QPLLLQDLLDQERQEQQQQRQMQAMIRQRSEPFFPNIDFDAITDPIMKAK 3100
3101 MVALKGINKVMAQNNLGMPPMVMSRFPFMGQVVTGTQNSEGQNLGPQAIP 3150
3151 QDGSITHQISRPNPPNFGPGFVNDSQRKQYEEWLQETQQLLQMQQKYLEE 3200
3201 QIGAHRKSKKALSAKQRTAKKAGREFPEEDAEQLKHVTEQQSMVQKQLEQ 3250
3251 IRKQQKEHAELIEDYRIKQQQQCAMAPPTMMPSVQPQPPLIPGATPPTMS 3300
3301 QPTFPMVPQQLQHQQHTTVISGHTSPVRMPSLPGWQPNSAPAHLPLNPPR 3350
3351 IQPPIAQLPIKTCTPAPGTVSNANPQSGPPPRVEFDDNNPFSESFQERER 3400
3401 KERLREQQERQRIQLMQEVDRQRALQQRMEMEQHGMVGSEISSSRTSVSQ 3450
3451 IPFYSSDLPCDFMQPLGPLQQSPQHQQQMGQVLQQQNIQQGSINSPSTQT 3500
3501 FMQTNERRQVGPPSFVPDSPSIPVGSPNFSSVKQGHGNLSGTSFQQSPVR 3550
3551 PSFTPALPAAPPVANSSLPCGQDSTITHGHSYPGSTQSLIQLYSDIIPEE 3600
3601 KGKKKRTRKKKRDDDAESTKAPSTPHSDITAPPTPGISETTSTPAVSTPS 3650
3651 ELPQQADQESVEPVGPSTPNMAAGQLCTELENKLPNSDFSQATPNQQTYA 3700
3701 NSEVDKLSMETPAKTEEIKLEKAETESCPGQEEPKLEEQNGSKVEGNAVA 3750
3751 CPVSSAQSPPHSAGAPAAKGDSGNELLKHLLKNKKSSSLLNQKPEGSICS 3800
3801 EDDCTKDNKLVEKQNPAEGLQTLGAQMQGGFGCGNQLPKTDGGSETKKQR 3850
3851 SKRTQRTGEKAAPRSKKRKKDEEEKQAMYSSTDTFTHLKQQNNLSNPPTP 3900
3901 PASLPPTPPPMACQKMANGFATTEELAGKAGVLVSHEVTKTLGPKPFQLP 3950
3951 FRPQDDLLARALAQGPKTVDVPASLPTPPHNNQEELRIQDHCGDRDTPDS 4000
4001 FVPSSSPESVVGVEVSRYPDLSLVKEEPPEPVPSPIIPILPSTAGKSSES 4050
4051 RRNDIKTEPGTLYFASPFGPSPNGPRSGLISVAITLHPTAAENISSVVAA 4100
4101 FSDLLHVRIPNSYEVSSAPDVPSMGLVSSHRINPGLEYRQHLLLRGPPPG 4150
4151 SANPPRLVSSYRLKQPNVPFPPTSNGLSGYKDSSHGIAESAALRPQWCCH 4200
4201 CKVVILGSGVRKSFKDLTLLNKDSRESTKRVEKDIVFCSNNCFILYSSTA 4250
4251 QAKNSENKESIPSLPQSPMRETPSKAFHQYSNNISTLDVHCLPQLPEKAS 4300
4301 PPASPPIAFPPAFEAAQVEAKPDELKVTVKLKPRLRAVHGGFEDCRPLNK 4350
4351 KWRGMKWKKWSIHIVIPKGTFKPPCEDEIDEFLKKLGTSLKPDPVPKDYR 4400
4401 KCCFCHEEGDGLTDGPARLLNLDLDLWVHLNCALWSTEVYETQAGALINV 4450
4451 ELALRRGLQMKCVFCHKTGATSGCHRFRCTNIYHFTCAIKAQCMFFKDKT 4500
4501 MLCPMHKPKGIHEQELSYFAVFRRVYVQRDEVRQIASIVQRGERDHTFRV 4550
4551 GSLIFHTIGQLLPQQMQAFHSPKALFPVGYEASRLYWSTRYANRRCRYLC 4600
4601 SIEEKDGRPVFVIRIVEQGHEDLVLSDISPKGVWDKILEPVACVRKKSEM 4650
4651 LQLFPAYLKGEDLFGLTVSAVARIAESLPGVEACENYTFRYGRNPLMELP 4700
4701 LAVNPTGCARSEPKMSAHVKRFVLRPHTLNSTSTSKSFQSTVTGELNAPY 4750
4751 SKQFVHSKSSQYRKMKTEWKSNVYLARSRIQGLGLYAARDIEKHTMVIEY 4800
4801 IGTIIRNEVANRKEKLYESQNRGVYMFRMDNDHVIDATLTGGPARYINHS 4850
4851 CAPNCVAEVVTFERGHKIIISSSRRIQKGEELCYDYKFDFEDDQHKIPCH 4900
4901 CGAVNCRKWMN 4911
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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