 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P11716 from www.uniprot.org...
The NucPred score for your sequence is 0.57 (see score help below)
1 MGDGGEGEDEVQFLRTDDEVVLQCSATVLKEQLKLCLAAEGFGNRLCFLE 50
51 PTSNAQNVPPDLAICCFTLEQSLSVRALQEMLANTVEAGVESSQGGGHRT 100
101 LLYGHAILLRHAHSRMYLSCLTTSRSMTDKLAFDVGLQEDATGEACWWTM 150
151 HPASKQRSEGEKVRVGDDLILVSVSSERYLHLSTASGELQVDASFMQTLW 200
201 NMNPICSCCEEGYVTGGHVLRLFHGHMDECLTISAADSDDQRRLVYYEGG 250
251 AVCTHARSLWRLEPLRISWSGSHLRWGQPLRIRHVTTGRYLALTEDQGLV 300
301 VVDACKAHTKATSFCFRVSKEKLDTAPKRDVEGMGPPEIKYGESLCFVQH 350
351 VASGLWLTYAAPDPKALRLGVLKKKAILHQEGHMDDALFLTRCQQEESQA 400
401 ARMIHSTAGLYNQFIKGLDSFSGKPRGSGPPAGPALPIEAVILSLQDLIG 450
451 YFEPPSEELQHEEKQSKLRSLRNRQSLFQEEGMLSLVLNCIDRLNVYTTA 500
501 AHFAEYAGEEAAESWKEIVNLLYELLASLIRGNRANCALFSTNLDWVVSK 550
551 LDRLEASSGILEVLYCVLIESPEVLNIIQENHIKSIISLLDKHGRNHKVL 600
601 DVLCSLCVCNGVAVRSNQDLITENLLPGRELLLQTNLINYVTSIRPNIFV 650
651 GRAEGSTQYGKWYFEVMVDEVVPFLTAQATHLRVGWALTEGYSPYPGGGE 700
701 GWGGNGVGDDLYSYGFDGLHLWTGHVARPVTSPGQHLLAPEDVVSCCLDL 750
751 SVPSISFRINGCPVQGVFEAFNLDGLFFPVVSFSAGVKVRFLLGGRHGEF 800
801 KFLPPPGYAPCHEAVLPRERLRLEPIKEYRREGPRGPHLVGPSRCLSHTD 850
851 FVPCPVDTVQIVLPPHLERIREKLAENIHELWALTRIEQGWTYGPVRDDN 900
901 KRLHPCLVNFHSLPEPERNYNLQMSGETLKTLLALGCHVGMADEKAEDNL 950
951 KKTKLPKTYMMSNGYKPAPLDLSHVRLTPAQTTLVDRLAENGHNVWARDR 1000
1001 VAQGWSYSAVQDIPARRNPRLVPYRLLDEATKRSNRDSLCQAVRTLLGYG 1050
1051 YNIEPPDQEPSQVENQSRWDRVRIFRAEKSYTVQSGRWYFEFEAVTTGEM 1100
1101 RVGWARPELRPDVELGADELAYVFNGHRGQRWHLGSEPFGRPWQSGDVVG 1150
1151 CMIDLTENTIIFTLNGEVLMSDSGSETAFREIEIGDGFLPVCSLGPGQVG 1200
1201 HLNLGQDVSSLRFFAICGLQEGFEPFAINMQRPVTTWFSKSLPQFEPVPP 1250
1251 EHPHYEVARMDGTVDTPPCLRLAHRTWGSQNSLVEMLFLRLSLPVQFHQH 1300
1301 FRCTAGATPLAPPGLQPPAEDEARAAEPDPDYENLRRSAGGWGEAEGGKE 1350
1351 GTAKEGTPGGTPQPGVEAQPVRAENEKDATTEKNKKRGFLFKAKKAAMMT 1400
1401 QPPATPALPRLPHDVVPADNRDDPEIILNTTTYYYSVRVFAGQEPSCVWV 1450
1451 GWVTPDYHQHDMNFDLSKVRAVTVTMGDEQGNVHSSLKCSNCYMVWGGDF 1500
1501 VSPGQQGRISHTDLVIGCLVDLATGLMTFTANGKESNTFFQVEPNTKLFP 1550
1551 AVFVLPTHQNVIQFELGKQKNIMPLSAAMFLSERKNPAPQCPPRLEVQML 1600
1601 MPVSWSRMPNHFLQVETRRAGERLGWAVQCQDPLTMMALHIPEENRCMDI 1650
1651 LELSERLDLQRFHSHTLRLYRAVCALGNNRVAHALCSHVDQAQLLHALED 1700
1701 AHLPGPLRAGYYDLLISIHLESACRSRRSMLSEYIVPLTPETRAITLFPP 1750
1751 GRKGGNARRHGLPGVGVTTSLRPPHHFSPPCFVAALPAAGVAEAPARLSP 1800
1801 AIPLEALRDKALRMLGEAVRDGGQHARDPVGGSVEFQFVPVLKLVSTLLV 1850
1851 MGIFGDEDVKQILKMIEPEVFTEEEEEEEEEEEEEEEEEEDEEEKEEDEE 1900
1901 EEEKEDAEKEEEEAPEGEKEDLEEGLLQMKLPESVKLQMCNLLEYFCDQE 1950
1951 LQHRVESLAAFAERYVDKLQANQRSRYALLMRAFTMSAAETARRTREFRS 2000
2001 PPQEQINMLLHFKDEADEEDCPLPEDIRQDLQDFHQDLLAHCGIQLEGEE 2050
2051 EEPEEETSLSSRLRSLLETVRLVKKKEEKPEEELPAEEKKPQSLQELVSH 2100
2101 MVVRWAQEDYVQSPELVRAMFSLLHRQYDGLGELLRALPRAYTISPSSVE 2150
2151 DTMSLLECLGQIRSLLIVQMGPQEENLMIQSIGNIMNNKVFYQHPNLMRA 2200
2201 LGMHETVMEVMVNVLGGGETKEIRFPKMVTSCCRFLCYFCRISRQNQRSM 2250
2251 FDHLSYLLENSGIGLGMQGSTPLDVAAASVIDNNELALALQEQDLEKVVS 2300
2301 YLAGCGLQSCPMLLAKGYPDIGWNPCGGERYLDFLRFAVFVNGESVEENA 2350
2351 NVVVRLLIRKPECFGPALRGEGGSGLLAAIEEAIRISEDPARDGPGVRRD 2400
2401 RRREHFGEEPPEENRVHLGHAIMSFYAALIDLLGRCAPEMHLIQAGKGEA 2450
2451 LRIRAILRSLVPLDDLVGIISLPLQIPTLGKDGALVQPKMSASFVPDHKA 2500
2501 SMVLFLDRVYGIENQDFLLHVLDVGFLPDMRAAASLDTATFSTTEMALAL 2550
2551 NRYLCLAVLPLITKCAPLFAGTEHRAIMVDSMLHTVYRLSRGRSLTKAQR 2600
2601 DVIEDCLMALCRYIRPSMLQHLLRRLVFDVPILNEFAKMPLKLLTNHYER 2650
2651 CWKYYCLPTGWANFGVTSEEELHLTRKLFWGIFDSLAHKKYDQELYRMAM 2700
2701 PCLCAIAGALPPDYVDASYSSKAEKKATVDAEGNFDPRPVETLNVIIPEK 2750
2751 LDSFINKFAEYTHEKWAFDKIQNNWSYGENVDEELKTHPMLRPYKTFSEK 2800
2801 DKEIYRWPIKESLKAMIAWEWTIEKAREGEEERTEKKKTRKISQTAQTYD 2850
2851 PREGYNPQPPDLSGVTLSRELQAMAEQLAENYHNTWGRKKKQELEAKGGG 2900
2901 THPLLVPYDTLTAKEKARDREKAQELLKFLQMNGYAVTRGLKDMELDTSS 2950
2951 IEKRFAFGFLQQLLRWMDISQEFIAHLEAVVSSGRVEKSPHEQEIKFFAK 3000
3001 ILLPLINQYFTNHCLYFLSTPAKVLGSGGHASNKEKEMITSLFCKLAALV 3050
3051 RHRVSLFGTDAPAVVNCLHILARSLDARTVMKSGPEIVKAGLRSFFESAS 3100
3101 EDIEKMVENLRLGKVSQARTQVKGVGQNLTYTTVALLPVLTTLFQHIAQH 3150
3151 QFGDDVILDDVQVSCYRTLCSIYSLGTTKNTYVEKLRPALGECLARLAAA 3200
3201 MPVAFLEPQLNEYNACSVYTTKSPRERAILGLPNSVEEMCPDIPVLDRLM 3250
3251 ADIGGLAESGARYTEMPHVIEITLPMLCSYLPRWWERGPEAPPPALPAGA 3300
3301 PPPCTAVTSDHLNSLLGNILRIIVNNLGIDEATWMKRLAVFAQPIVSRAR 3350
3351 PELLHSHFIPTIGRLRKRAGKVVAEEEQLRLEAKAEAEEGELLVRDEFSV 3400
3401 LCRDLYALYPLLIRYVDNNRAHWLTEPNANAEELFRMVGEIFIYWSKSHN 3450
3451 FKREEQNFVVQNEINNMSFLTADSKSKMAKAGDAQSGGSDQERTKKKRRG 3500
3501 DRYSVQTSLIVATLKKMLPIGLNMCAPTDQDLIMLAKTRYALKDTDEEVR 3550
3551 EFLQNNLHLQGKVEGSPSLRWQMALYRGLPGREEDADDPEKIVRRVQEVS 3600
3601 AVLYHLEQTEHPYKSKKAVWHKLLSKQRRRAVVACFRMTPLYNLPTHRAC 3650
3651 NMFLESYKAAWILTEDHSFEDRMIDDLSKAGEQEEEEEEVEEKKPDPLHQ 3700
3701 LVLHFSRTALTEKSKLDEDYLYMAYADIMAKSCHLEEGGENGEAEEEEVE 3750
3751 VSFEEKEMEKQRLLYQQSRLHTRGAAEMVLQMISACKGETGAMVSSTLKL 3800
3801 GISILNGGNAEVQQKMLDYLKDKKEVGFFQSIQALMQTCSVLDLNAFERQ 3850
3851 NKAEGLGMVNEDGTVINRQNGEKVMADDEFTQDLFRFLQLLCEGHNNDFQ 3900
3901 NYLRTQTGNTTTINIIICTVDYLLRLQESISDFYWYYSGKDVIEEQGKRN 3950
3951 FSKAMSVAKQVFNSLTEYIQGPCTGNQQSLAHSRLWDAVVGFLHVFAHMM 4000
4001 MKLAQDSSQIELLKELLDLQKDMVVMLLSLLEGNVVNGMIARQMVDMLVE 4050
4051 SSSNVEMILKFFDMFLKLKDIVGSEAFQDYVTDPRGLISKKDFQKAMDSQ 4100
4101 KQFTGPEIQFLLSCSEADENEMINFEEFANRFQEPARDIGFNVAVLLTNL 4150
4151 SEHVPHDPRLRNFLELAESILEYFRPYLGRIEIMGASRRIERIYFEISET 4200
4201 NRAQWEMPQVKESKRQFIFDVVNEGGEAEKMELFVSFCEDTIFEMQIAAQ 4250
4251 ISEPEGEPEADEDEGMGEAAAEGAEEGAAGAEGAAGTVAAGATARLAAAA 4300
4301 ARALRGLSYRSLRRRVRRLRRLTAREAATALAALLWAVVARAGAAGAGAA 4350
4351 AGALRLLWGSLFGGGLVEGAKKVTVTELLAGMPDPTSDEVHGEQPAGPGG 4400
4401 DADGAGEGEGEGDAAEGDGDEEVAGHEAGPGGAEGVVAVADGGPFRPEGA 4450
4451 GGLGDMGDTTPAEPPTPEGSPILKRKLGVDGEEEELVPEPEPEPEPEPEK 4500
4501 ADEENGEKEEVPEAPPEPPKKAPPSPPAKKEEAGGAGMEFWGELEVQRVK 4550
4551 FLNYLSRNFYTLRFLALFLAFAINFILLFYKVSDSPPGEDDMEGSAAGDL 4600
4601 AGAGSGGGSGWGSGAGEEAEGDEDENMVYYFLEESTGYMEPALWCLSLLH 4650
4651 TLVAFLCIIGYNCLKVPLVIFKREKELARKLEFDGLYITEQPGDDDVKGQ 4700
4701 WDRLVLNTPSFPSNYWDKFVKRKVLDKHGDIFGRERIAELLGMDLASLEI 4750
4751 TAHNERKPDPPPGLLTWLMSIDVKYQIWKFGVIFTDNSFLYLGWYMVMSL 4800
4801 LGHYNNFFFAAHLLDIAMGVKTLRTILSSVTHNGKQLVMTVGLLAVVVYL 4850
4851 YTVVAFNFFRKFYNKSEDEDEPDMKCDDMMTCYLFHMYVGVRAGGGIGDE 4900
4901 IEDPAGDEYELYRVVFDITFFFFVIVILLAIIQGLIIDAFGELRDQQEQV 4950
4951 KEDMETKCFICGIGSDYFDTTPHGFETHTLEEHNLANYMFFLMYLINKDE 5000
5001 TEHTGQESYVWKMYQERCWDFFPAGDCFRKQYEDQLS 5037
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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