 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9P2P6 from www.uniprot.org...
The NucPred score for your sequence is 0.95 (see score help below)
1 MANVQVAVRVRPLSKRETKEGGRIIVEVDGKVAKIRNLKVDNRPDGFGDS 50
51 REKVMAFGFDYCYWSVNPEDPQYASQDVVFQDLGMEVLSGVAKGYNICLF 100
101 AYGQTGSGKTYTMLGTPASVGLTPRICEGLFVREKDCASLPSSCRIKVSF 150
151 LEIYNERVRDLLKQSGQKKSYTLRVREHPEMGPYVQGLSQHVVTNYKQVI 200
201 QLLEEGIANRITAATHVHEASSRSHAIFTIHYTQAILENNLPSEMASKIN 250
251 LVDLAGSERADPSYCKDRIAEGANINKSLVTLGIVISTLAQNSQVFSSCQ 300
301 SLNSSVSNGGDSGILSSPSGTSSGGAPSRRQSYIPYRDSVLTWLLKDSLG 350
351 GNSKTIMVATVSPAHTSYSETMSTLRYASSAKNIINKPRVNEDANLKLIR 400
401 ELREEIERLKALLLSFELRNFSSLSDENLKELVLQNELKIDQLTKDWTQK 450
451 WNDWQALMEHYSVDINRRRAGVVIDSSLPHLMALEDDVLSTGVVLYHLKE 500
501 GTTKIGRIDSDQEQDIVLQGQWIERDHCTITSACGVVVLRPARGARCTVN 550
551 GREVTASCRLTQGAVITLGKAQKFRFNHPAEAAVLRQRRQVGEAAAGRGS 600
601 LEWLDLDGDLAASRLGLSPLLWKERRALEEQCDEDHQTPRDGETSHRAQI 650
651 QQQQSYVEDLRHQILAEEIRAAKELEFDQAWISQQIKENQQCLLREETWL 700
701 ASLQQQQQEDQVAEKELEASVALDAWLQTDPEIQPSPFVQSQKRVVHLQL 750
751 LRRHTLRAAERNVRRKKVSFQLERIIKKQRLLEAQKRLEKLTTLCWLQDD 800
801 STQEPPYQVLSPDATVPRPPCRSKLTSCSSLSPQRLCSKHMPQLHSIFLS 850
851 WDPSTTLPPRPDPTHQTSEKTSSEEHLPQAASYPARTGCLRKNGLHSSGH 900
901 GQPCTARAALARKGASAPDACLTMSPNSVGIQEMEMGVKQPHQMVSQGLA 950
951 SLRKSANKLKPRHEPKIFTSTTQTRGAKGLADPSHTQAGWRKEGNLGTHK 1000
1001 AAKGASCNSLYPHGPRQTAGHGKAVKTFWTEYKPPSPSRASKRHQRVLAT 1050
1051 RVRNITKKSSHLPLGSPLKRQQNTRDPDTMVPLTDFSPVMDHSREKDNDL 1100
1101 SDTDSNYSLDSLSCVYAKALIEPLKPEERKWDFPEPENSESDDSQLSEDS 1150
1151 LAEKRYQSPKNRLGGNRPTNNRGQPRTRTRASVRGFTAASDSDLLAQTHR 1200
1201 SFSLDSLIDAEEELGEDQQEEPFPGSADEIPTETFWHLEDSSLPVMDQEA 1250
1251 ICRLGPINYRTAARLDAVLPMSSSFYLDPQFQPHCELQPHCELQPHCELQ 1300
1301 PHCEQAESQVEPSYSEQADSLQGMQLSRESPLMSMDSWFSCDSKINPSSP 1350
1351 PGIVGSLCPSPDMQEFHSCKGERPGYWPNTEELKPSDAETVLPYSSKLHQ 1400
1401 GSTELLCSARDEHTASAADTSRLSLWGIQRLIQPGADGTFQGRCIPDMTQ 1450
1451 QGSSEASHNSSVSNVLAASATTLTHVGSTHERDWSALQQKYLLELSCPVL 1500
1501 EAIGAPKPAYPYLEEDSGSLAQASSKGGDTLLPVGPRVSSNLNLNNFPVH 1550
1551 LSRIRRLRAEKEQDSLNAKLEGVSDFFSTSEKEASYDETYSADLESLSAS 1600
1601 RSTNAQVFATENAIPDSMTEACEVKQNNLEECLQSCRKPGLMTSSDEDFF 1650
1651 QKNACHSNVTTATKADHWSQGWAPLRKNSAVQPGQLSPDSHYPLEEEKTD 1700
1701 CQESSKEAVRRHINVSFALPSGPELYLHSAPWNPLSSSLQPPLLETFYVT 1750
1751 KSRDALTETALEIPACREVRVPSPPPREAWGFGHNHQALQGAYLKNNLPV 1800
1801 LLQNQNSKIASSQQVTAEIPVDLNTREVIRESGKCPGNITEESHDSVYSS 1850
1851 VTQNRHFLPSTSTKVCEFENQVVILNKKHSFPALEGGEVTAQSCCGASSD 1900
1901 STESGKSLLFRESEAREEEELDQNTVLRQTINVSLEKDMPGESAVSLKSR 1950
1951 SVDRRVSSPVMVAQGGGPTPKWEGKNETGLLEKGLRPKDSSEEFKLPGTK 2000
2001 PAYERFQLVACPQERNPSECKSQEMLNPNREPSGKKQNKRVNNTDEMARL 2050
2051 IRSVMQLENGILEIESKQNKQVHASHTPGTDKELVFQDQKEQEKTDHAFR 2100
2101 PDSSGNPLPSKDQPSSPRQTDDTVFRDSEAGAMEVNSIGNHPQVQKITPN 2150
2151 PFRSREGVRESEPVREHTHPAGSDRPARDICDSLGKHTTCREFTNTSLHP 2200
2201 QRMKALARALPLQPRLERSSKNNGQFVKASASLKGQPWGLGSLEELETVK 2250
2251 GFQESQVAEHVSSSNQEEPKAQGKVEEMPMQRGGSLQEENKVTQKFPSLS 2300
2301 QLCRDTFFRQETVSPLLSRTEFCTAPLHQDLSNTLPLNSPRWPRRCLHVP 2350
2351 VALGISSLDCVLDLTMLKIHNSPLVTGVEHQDQSTETRSHSPEGNVRGRS 2400
2401 SEAHTAWCGSVRSMAMGSHSQSGVPESIPLGTEDRISASTSPQDHGKDLR 2450
2451 ITLLGFSTSEDFASEAEVAVQKEIRVSSLNKVSSQPEKRVSFSLEEDSDQ 2500
2501 ASKPRQKAEKETEDVGLTSGVSLAPVSLPRVPSPEPRLLEPSDHASMCLA 2550
2551 ILEEIRQAKAQRKQLHDFVARGTVLSYCETLLEPECSSRVAGRPQCKQID 2600
2601 QSSSDQTRNEGEAPGFHVASLSAEAGQIDLLPDERKVQATSLSADSFESL 2650
2651 PNTETDREPWDPVQAFSHAAPAQDRKRRTGELRQFAGASEPFICHSSSSE 2700
2701 IIEKKKDATRTPSSADPLAPDSPRSSAPVEEVRRVVSKKVVAALPSQAPY 2750
2751 DDPRVTLHELSQSVPQETAEGIPPGSQDSSPEHQEPRTLDTTYGEVSDNL 2800
2801 LVTAQGEKTAHFESQSVTCDVQNSTSASGPKQDHVQCPEASTGFEEGRAS 2850
2851 PKQDTILPGALTRVALEAPTQQCVQCKESVGSGLTEVCRAGSKHSRPIPL 2900
2901 PDQRPSANPGGIGEEAPCRHPREALDGPVFSRNPEGSRTLSPSRGKESRT 2950
2951 LPCRQPCSSQPVATHAYSSHSSTLLCFRDGDLGKEPFKAAPHTIHPPCVV 3000
3001 PSRAYEMDETGEISRGPDVHLTHGLEPKDVNREFRLTESSTCEPSTVAAV 3050
3051 LSRAQGCRSPSAPDVRTGSFSHSATDGSVGLIGVPEKKVAEKQASTELEA 3100
3101 ASFPAGMYSEPLRQFRDSSVGDQNAQVCQTNPEPPATTQGPHTLDLSEGS 3150
3151 AESKLVVEPQHECLENTTRCFLEKPQFSTELRDHNRLDSQAKFVARLKHT 3200
3201 CSPQEDSPWQEEEQHRDQASGGGEGFAQGVNPLPDEDGLDGCQILDAGRE 3250
3251 EVAVAKPPVSKILSQGFKDPATVSLRQNETPQPAAQRSGHLYTGREQPAP 3300
3301 NHRGSLPVTTIFSGPKHSRSSPTPQFSVVGSSRSLQELNLSVEPPSPTDE 3350
3351 DTQGPNRLWNPHLRGYSSGKSVARTSLQAEDSNQKASSRLDDGTTDHRHL 3400
3401 KPATPPYPMPSTLSHMPTPDFTTSWMSGTLEQAQQGKREKLGVQVRPENW 3450
3451 CSQMDKGMLHFGSSDISPYALPWRPEEPARISWKQYMSGSAVDVSCSQKP 3500
3501 QGLTLSNVARCSSMDNGLEDQNSPFHSHLSTYANICDLSTTHSSTENAQG 3550
3551 SNEAWEVFRGSSSIALGDPHIPTSPEGVAPTSGHDRRPQFRGPSGEADCL 3600
3601 RSKPPLAKGSAAGPVDEIMLLYPSEAGCPVGQTRTNTFEQGTQTLGSRRH 3650
3651 WSSTDISFAQPEASAVSAFDLASWTSMHNLSLHLSQLLHSTSELLGSLSQ 3700
3701 PDVARREQNTKRDIPDKAPQALMMDGSTQTTVDEGSQTDLTLPTLCLQTS 3750
3751 EAEPQGANVILEGLGSDTSTVSQEEGDVPGVPQKREAEETAQKMAQLLYL 3800
3801 QEESTPYKPQSPSIPSSHLRFQKAPVGQHLPSVSPSVSDAFLPPSSQPEE 3850
3851 SYCLVVSSPSPSSPHSPGLFPSTSEYPGDSRVQKKLGPTSALFVDRASSP 3900
3901 ILTLSASTQEPGLSPGSLTLSAPSTHPVEGHQKLDSSPDPVDAPRTPMDN 3950
3951 YSQTTDELGGSQRGRSSLQRSNGRSFLELHSPHSPQQSPKLQFSFLGQHP 4000
4001 QQLQPRTTIGVQSRLLPPPLRHRSQRLGNSFVPEKVASPEHCPLSGREPS 4050
4051 QWQSRTENGGESSASPGEPQRTLDRPSSWGGLQHLSPCPVSELTDTAGLR 4100
4101 GSALGLPQACQPEELLCFSCQMCMAPEHQHHSLRDLPVHNKFSNWCGVQK 4150
4151 GSPGGLDMTEEELGASGDLSSEKQEQSPPQPPNDHSQDSEWSKREQIPLQ 4200
4201 VGAQNLSLSVELTEAKLHHGFGEADALLQVLQSGTGEALAADEPVTSTWK 4250
4251 ELYARQKKAIETLRRERAERLGNFCRTRSLSPQKQLSLLPNKDLFIWDLD 4300
4301 LPSRRREYLQQLRKDVVETTRSPESVSRSAHTPSDIELMLQDYQQAHEEA 4350
4351 KVEIARARDQLRERTEQEKLRIHQKIISQLLKEEDKLHTLANSSSLCTSS 4400
4401 NGSLSSGMTSGYNSSPALSGQLQFPENMGHTNLPDSRDVWIGDERGGHSA 4450
4451 VRKNSAYSHRASLGSCCCSPSSLSSLGTCFSSSYQDLAKHVVDTSMADVM 4500
4501 AACSDNLHNLFSCQATAGWNYQGEEQAVQLYYKVFSPTRHGFLGAGVVSQ 4550
4551 PLSRVWAAVSDPTVWPLYYKPIQTARLHQRVTNSISLVYLVCNTTLCALK 4600
4601 QPRDFCCVCVEAKEGHLSVMAAQSVYDTSMPRPSRKMVRGEILPSAWILQ 4650
4651 PITVEGKEVTRVIYLAQVELGAPGFPPQLLSSFIKRQPLVIARLASFLGR 4700
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.) |
Go back to the NucPred Home Page.