 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q24498 from www.uniprot.org...
The NucPred score for your sequence is 0.73 (see score help below)
1 MAEAEGGSEQDDVSFLRTEDMVTLSCTATGERVCLAAEGFGNRHCFLENI 50
51 ADKNVPPDLSQCVFVIEQALSVRALQELVTAAGSETGKGTGSGHRTLLYG 100
101 NAILLRHHNSDMYLACLSTSSSNDKLSFDVGLQEHSQGEACWWTVHPASK 150
151 QRSEGEKVRVGDDLILVSVATERYLHTTKENEQSIVNASFHVTHWSVQPY 200
201 GTGISRMKYVGYVFGGDVLRFFHGGDECLTIPSTWGREAGQNIVIYEGGV 250
251 VMAQARSLWRLELARTKWTGGFINWYHPMRIRHITTGRYLGVNDSNELIL 300
301 VKKEEASIATTTFCLRQEKDDEKKVLEDKDLEVIGSPIIKYGDTTVIVQH 350
351 CETSLWLSYKSYETKKKGVGKVEEKQAILHEEGKMDDCLDFSRSQEEESK 400
401 TARVIRKCSSLFTQFITALETLQSNRRHSIFFQKVNLNEMVMCLEDLINY 450
451 FSQPEDDMEHEEKQNRFRALRNRQDLFQEEGVLNLILEAIDKINIITSQG 500
501 FLASFLAGDETGQSWDLISTYLYQLLAAIIKGNHTNCAQFANSNRLNWLF 550
551 SRLGSQASSEGSGMLDVLHCVLIDSPEALNMMRDEHIKVIISLLEKHGRD 600
601 PKVLDVLCSLCVGNGVAVRSSQNNICDFLLPGKNLLLQTLLVDHVASIRP 650
651 NIFVGRVDGSSMYQKWYFEVTMDHIEQTTHMMPHLRIGWANTSGYVPYPG 700
701 GGKKWGGNGVGDDLYSFGFDGAFLWTGGRKTLVVDALPEEPFIRKGDVIG 750
751 VAIDLSVPIITFTFNGVKVRGSFRDFNLDGMFFPVMSCSSKLSCRFLFGG 800
801 DHGRLKFAPPMGFSALVQCLMPQQILSLDPCFYFGNLAKNVLAGPWLIED 850
851 DTAFVPKPVDTTGVTLPSSVDQIKEKLAENIHEMWALNKIEAGWSWGEHR 900
901 DDYHRIHPCLTHFEKLPAAEKRYDNQLAVQTLKTIISLGYYITMDKPPAR 950
951 IRPVRLPNEIFMQGNGYKPAPLDLSAVTLTPKLEELVDQLAENTHNLWAR 1000
1001 ERIQQGWTYGLNEDSENHRSPHLVPYAKVDEAIKKANRDTASETVRTLLV 1050
1051 YGYVLDPPTGEGTEALLAEAQRLKFAGFRTYRVERNYAVTSGKWYFEFEV 1100
1101 LTSGPMRVGWARADCYPGAMLGSEDTSWAFDGHNVTKMHAGSIEHFGVRY 1150
1151 EAGDVIGCFIDVKEQTISFSLNGELLMDALGGETTFADVTAEGVGFVPAC 1200
1201 TLGVGQKARLIYGQDVDSLKFFTTCGLQEGYEPFCVNMRRPVTHWYTKDQ 1250
1251 PIFENTEEMPDCRIDVTRIPGGADTPPHLKISHNTFETMEKANWEFLRLS 1300
1301 LPVTCMGEFISEQEKARRWDEIKNRQYRLMREAEIAAQMQVQTQAAHMDH 1350
1351 MLKGGFNMNDIKGLTRNFDEHADAEADHMMRGPNRPPRKGSLTRNITFET 1400
1401 DMSAALDEMQRSTSVLDMNGLGEEMDDKKKRGRSPFKFFSKKSRDQSREK 1450
1451 MGARTLDTSLERRNTVAHGRNVVNQQMTTRAPTLRLNNAEIPPSPVPQGP 1500
1501 KQLSGSNLGQQPVETSGDEMFDAECLKLINEYFYGVRIFPGQDPTHVYVG 1550
1551 WVTTQYHLHSREFNKNKVRRGSVYIEDDYEMAIERIDRQSCYVVRADELF 1600
1601 NEVTQDASGKGASQGMFVGCFVDTATGIIRFTCEGKDTSHRWMMEPDTKL 1650
1651 FPAIFVEATSKEILQIELGRTPTTLPLSAAVLPTSDKHINPQSPPRLKVQ 1700
1701 CLRPHQWARVPNTALQVHALKLSDVRGWSMLCEDPVSMLALHIPEEDRCI 1750
1751 DILELIEMDKLLSFHAHSLTLYAALCYQSNYRAAHALCQHVDQKQLLYAI 1800
1801 RSEYMSGPLRQGFYDLLIALHLESHATTMEVCKNEYITPLGAELKELYSD 1850
1851 EEMQHSLRSLVTESVRPQLRMTEITPPVIATSSMPSVSSEPIPDIDQLYS 1900
1901 PKFPLEVVRQFVMEALKDAVEINQVHNRDPIGWTNENLFLPLIKLTDRLL 1950
1951 LVGVLTDEDVQRLLVMIDPETWDQAFEREGKDEHRKGLLTMKMAEGAKLQ 2000
2001 MCYLLHHLYDTQLRHRVESIIAFSHDFVGDLQTDQLRRYIEIKQSDLPSA 2050
2051 VAAKKTKEFRCPPREQMNQILCFKNLEPDDQDNCTCGLELRGRLGDFHDS 2100
2101 LMQKVSLNALQEPDGVEGTAIEEVKTGPITKIYNFINTVKELEEGPKEVE 2150
2151 EPEKKTPEEVFRKVLIKTIVSWAEESQIENPKLVREMFSLLLRQYDTVGE 2200
2201 LVRALEKTYVINTRARDDVAEMWVGLSQIRALLPVQMSQEEEELMRKRLW 2250
2251 KLVNNATFFQHPDLIRILRVHENVMAVMMNTLGRRAQAQSDAPTQSEVAE 2300
2301 GAPSKEKDTSHEMVVACCRFLCYFCRTGRQNQKAMFDHFDFLLDNANILL 2350
2351 ARPSLRGSTPLDVAYSSLMENTELALALREHYLEKIAVYLSRCGLQSNSE 2400
2401 LVEKGYPDLGWDPVEGERYLDFLRYCVWVNGESVEENANLVIRLLIRRPE 2450
2451 CLGPALRGEGEGLFRAIVEANRMSERISDRCKMQDEAEGTIAGLNFTHPL 2500
2501 PEGEEDEDYIDTGAAILNFYCTLVDLLGRCAPDASVIEQGKNESLRARAI 2550
2551 LRSLVPLEDLQGVLSLKFTLSQTAPGEEKPKSDMPSGLLPNNKQSIVLFL 2600
2601 ERVYGIEAQDLFYRLLEDAFLPDLRTATILDKSDGSESDMALAMNRYIGN 2650
2651 SILPLLIKHSKFYNEAENYASLLDATLHTVYRLSKNRMLTKGQREAVSDF 2700
2701 LVALTSQMQPAMLLKLLRKLTVDVSKLSEYTTVALRLLTLHFDRCAKYYG 2750
2751 STQGQGSYGASSDEEKRLTMLLFSNIFDSLSNMDYDPELFGKALPCLIAI 2800
2801 GCALPPDYSLSKNTDEDYYGRQMGAPDQPQYMPNPIDTNNVHLDNDLNSL 2850
2851 VQKFSEHYHDAWASRRLEGGWTYGDIRSDNDRKHPRLKPYNMLSEYERER 2900
2901 YRDPVRECLKGLLAIGWTVEHSEVEVALNHRGSTRRQSKPQINEFQNEGS 2950
2951 PFNYNPHPVDMSNLTLSREMQNMAERLAENSHDIWAKKKNEELNGCGGVI 3000
3001 HPQLVPYDLLTDKEKKKDRERSQEFLKYMQYQGYKLHKPSKGGAVEEGGA 3050
3051 TQAAVELRFSYSLLEKLIQYLDRATINMKLLKPSTTFSRRSSFKTATRDI 3100
3101 KFFSKVVLPLMEKYFSTHRNYFIAIATATNNIGAASLKEKEMVASIFCKL 3150
3151 AALLRNRLSAFGPDVRITVRCLQVLVKGIDARTLTKNCPEFIRTSMLTFF 3200
3201 NQTSDDLGNTILNLQDGKYSHLRGTHLKTSTSLGYVNQVVLPVLTAMFDH 3250
3251 LAACDYGSDLLLDEIQVASYKILAALYHLGTDGTLTHDRKYLKTEIERHR 3300
3301 PALGSCLGAYSSCFPVAFLEPHLNKHNQYSLLNRIADHSLEAQDIMVKME 3350
3351 SCMPNLETILAEVDQFVESDKTYNDAPHIIDVILPLLCAYLPFWWSQGPD 3400
3401 NVSPTSGNHVTMVTADHMNPLLRNVLKMIKKNIGNDNAPWMTRIAAYTQQ 3450
3451 IIINTSEELLKDPFLPLAERVKKRTENMLHKEDSMRGFIKSATDDTSQVE 3500
3501 TQLQEDWNLLVRDIYSFYPLLIKYVDLQRNHWLKDNIPEAEELYNHVAEI 3550
3551 FNIWSKSQYFLKEEQNFISANEIDNMALIMPTATRRSAISEGAPAVGGKV 3600
3601 KKKKKNRDKKRDKDKEVQASLMVACLKRLLPVGLNLFAGREQELVQHCKD 3650
3651 RYLKKMPEYDVIEFARNQLTLPDKLDPSDEMSWQHYLYSKLGKTEEPVDE 3700
3701 QALEKANVNSNEKGKDKTQETVDRIVAMAKVLFGLHMIDHPQQQSKNVYR 3750
3751 SVVSIQRKRAVIACFRQTSLHSLPRHRACNIFARSYYEQWLQEENVGQEV 3800
3801 MVEDLTQTFEDSEKSKKEGEETDSKPDPLTQLVTTFCRGAMTERSGALQE 3850
3851 DLLYMSYAQIAAKSTGKEEEEGGDEEGGEGGEEGEGTSIHEQEMEKQKLL 3900
3901 FHQARLSNRGVAEMVLLHISASKGIPSEMVMTTLNLGIAILRGGNIDIQM 3950
3951 GMLNHLKEKKDVGFFTSIAGLMNSCSVLDLDAFERNTKAEGLGVGSEGAA 4000
4001 GEKNMHDAEFTCALFRFIQLTCEGHNLEWQNYLRTQAGNTTTVNVVICTV 4050
4051 DYLLRLQESIMDFYWHYSSKEIIDPAGKANFFKAIEVASQVFNTLTEVIQ 4100
4101 GPCTLNQQALAHSRLWDAVGGFLFLFSHMQDKLSKHSSQVDLLKELLNLQ 4150
4151 KDMITMMLSMLEGNVVNGTIGKQMVDTLVESASNVELILKYFDMFLKLAD 4200
4201 LIESPSFHEVDMKNEGWVTPKDFREKMEQSKNYTPEEMDFLLACCERNHE 4250
4251 GKIDYRAFVEHFHEPSKEIGFNLAVLLTNLSEHMPNEPRLARFLETAGSV 4300
4301 LNYFEPFLGRIEILGSSKRIERVYFEIKDSNIEQWEKPQIRESKRAFFYS 4350
4351 IVTEGGDKEKLEAFVNFCEDAIFEMTHASGLMATDDGGGNVKRDTAYSSY 4400
4401 MSEEEEERAARDPIRRTITAVKEGLKFGVHMLSPANIKHQIGVMQTKSIP 4450
4451 ELIVGFFKIIFYIFYYTGYAHFCVVRYIFGILLNLMRGPAPEQEEEPVVE 4500
4501 EETFGRALPPLPLEEPPGTVQAFGLDINKEENGMYKVVVHESPANSSMEE 4550
4551 GGESSPEDGAAASGELVEGEPHQEPISIVDLLGGEAAKKAAQERQEAQKA 4600
4601 QEAAMASIEAEAKKSSSAPQETPAVHQIDFSQYTHRAVSFLARNFYNLKY 4650
4651 VALVLAFSINFMLLFYKVTSFTEEADSSAEEELILGSGSGGGADITGSGF 4700
4701 GGSGDGGSGDGEMEDEIPELVHVDEDFFYMEHVLRIAACLHSLVSLAMLI 4750
4751 AYYHLKVPLAIFKREKEIARRLEFEGLFIAEQPEDDDFKSHWDKLVISAK 4800
4801 SFPVNYWDKFVKKKVRQKYSETYDFDSISNLLGMEKSTFAAQESEETGIF 4850
4851 KYIMNIDWRYQVWKAGVTFTDNAFLYSLWYFSFSVMGNFNNFFFAAHLLD 4900
4901 VAVGFKTLRTILQSVTHNGKQLVLTVMLLTIIVYIYTVIAFNFFRKFYIQ 4950
4951 EEDEEVDKKCHDMLTCFVFHLYKGVRAGGGIGDEIGDPDGDDYEVYRIIF 5000
5001 DITFFFFVIIILLAIIQGLIIDAFGELRDQLESVKDNMESNCFICGMGKD 5050
5051 FFDIVPHGFDTHVQKEHNLANYMFFLMHLINKPDTEYTGQETYVWNMYQQ 5100
5101 RSWDFFPVGDCFRKQYEDELSGGGGGG 5127
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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