 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P16960 from www.uniprot.org...
The NucPred score for your sequence is 0.58 (see score help below)
1 MGDGGEGEDEVQFLRTDDEVVLQCNATVLKEQLKLCLAAEGFGNRLCFLE 50
51 PTSNAQNVPPDLAICCFVLEQSLSVRALQEMLANTVEAGVESSQGGGHRT 100
101 LLYGHAILLRHAHSGMYLSCLTTSRSMTDKLAFDVGLQEDATGEACWWTT 150
151 HPASKQRSEGEKVRVGDDLILVSVSSERYLHLSTASGELQVDASFMQTLW 200
201 NMNPICSGCEEGYVTGGHVLRLFHGHMDECLTISPADSDDQRRLVYYEGG 250
251 SVCTHARSLWRLEPLRISWSGSHLRWGQPLRIRHVTTGRYLALIEDQGLV 300
301 VVDASKAHTKATSFCFRISKEKLDTAPKRDVEGMGPPEIKYGESLCFVQH 350
351 VASGLWLTYAAPDPKALRLGVLKKKAILHQEGHMDDALSLTRCQQEESQA 400
401 ARMIYSTAGLYNHFIKGLDSFSGKPRGSGAPAGTALPLEGVILSLQDLIG 450
451 YFEPPSEELQHEEKQSKLRSLRNRQSLFQEEGMLSLVLNCIDRLNVYTTA 500
501 AHFAEFAGEEAAESWKEIVNLLYEILASLIRGNRANCALFSNNLDWLVSK 550
551 LDRLEASSGILEVLYCVLIESPEVLNIIQENHIKSIISLLDKHGRNHKVL 600
601 DVLCSLCVCNGVAVRSNQDLITENLLPGRELLLQTNLINYVTSIRPNIFV 650
651 GRAEGTTQYSKWYFEVMVDEVVPFLTAQATHLRVGWALTEGYSPYPGGGE 700
701 GWGGNGVGDDLYSYGFDGLHLWTGHVPRLVTSPGQHLLAPEDVVSCCLDL 750
751 SVPSISFRINGCPVQGVFEAFNLNGLFFPVVSFSAGVKVRFLLGGRHGEF 800
801 KFLPPPGYAPCHEAVLPRERLRLEPIKEYRREGPRGPHLVGPSRCLSHTD 850
851 FVPCPVDTVQIVLPPHLERIREKLAENIHELWALTRIEQGWTYGPVRDDN 900
901 KRLHPCLVDFHSLPEPERNYNLQMSGETLKTLLALGCHVGMADEKAEDNL 950
951 RKTKLPKTYMMSNGYKPAPLDLSHVRLTPAQTTLVDRLAENGHNVWARDR 1000
1001 VAQGWSYSAVQDIPARRNPRLVPYRLLDEATKRSNRDSLCQAVRTLLGYG 1050
1051 YNIEPPDQEPSQVESQSRWDRVRIFRAEKSYAVQSGRWYFEFEAVTTGEM 1100
1101 RVGWARPELRPDVELGADELAYVFNGHRGQRWHLGSELFGRPWQSGDVVG 1150
1151 CMIDLTENTIIFTLNGEVLMSDSGSETAFRDIEVGDGFLPVCSLGPGQVG 1200
1201 HLNLGQDVSSLRFFAICGLQEGFEPFAINMQRPVTTWFSKSLPQFEAVPL 1250
1251 EHPHYEVSRVDGTVDTPPCLRLTHRTWGSQNSLVEMLFLRLSLPVQFHQH 1300
1301 FRCTAGATPLAPPGLQPPAEDEARAAEPDPDYENLRRSAGRWGEAEGGKE 1350
1351 GTAKEGAPGGTAQAGVEAQPPRAENEKDATTEKNKKRGFLFKAKKAAMMT 1400
1401 QPPATPTLPRLPHEVVPADDRDDPDIILNTTTYYYSVRVFAGQEPSCVWV 1450
1451 GWVTPDYHQHDMNFDLTKVRAVTVTMGDEQGNIHSSLKCSNCYMVWGGDF 1500
1501 VSPGQQGRISHTDLVIGCLVDLATGLMTFTANGKESNTFFQVEPNTKLFP 1550
1551 AVFVLPTHQNVIQFELGKQKNIMPLSAAMFLSERKNPAPQCPPRLEMQML 1600
1601 MPVSWSRMPNHFLRVETRRAGERLGWAVQCQEPLTMMALHIPEENRCMDI 1650
1651 LELSERLDLQQFHSHTLRLYRAVCALGNNRVAHALCSHVDQAQLLHALED 1700
1701 AHLPGPLRAGYYDLLISIHLESACRSRRSMLSEYIVPLTPETRAITLFPP 1750
1751 GKRTENGPRRHGLPGVGVTTSLRPPHHFSAPCFVAALPAVGAAEAPARLS 1800
1801 PSIPLEALRDKALRMLGEAVRDGGQHARDPVGGSVEFQFVPVLKLVSTLL 1850
1851 VMGIFGDEDVKQILKMIEPEVFTEEEEEEEEEEEEEEEDEEEKEEDEEEE 1900
1901 AREKEDEEKEEEETAEGEKEEYLEEGLLQMKLPESVKLQMCNLLEYFCDQ 1950
1951 ELQHRVESLAAFAERYVDKLQANQRDRYGILMKAFTMTAAETARRTREFR 2000
2001 SPPQEQINMLLHFKDGEDEEDCPLPDEIRQDLLEFHQDLLTHCGIQLEGE 2050
2051 EEEPEEEATLGSRLMSLLEKVRLVKKKEEKSEEEPPAEESKAQSLQELVS 2100
2101 HTVVRWAQEDFVQSPELVRAMFSLLHRQYDGLGELLRALPRAYTISPSSV 2150
2151 EDTMSLLECLGQIRSLLIVQMGPQEENLMIQSIGNIMNNKVFYQHPNLMR 2200
2201 ALGMHETVMEVMVNVLGGGESKEIRFPKMVTSCCRFLCYFCRISRQNQRS 2250
2251 MFDHLSYLLENSGIGLGMQGSTPLDVAAASVIDNNELALALQEQDLEKVV 2300
2301 SYLAGCGLQSCPMLLAKGYPDIGWNPCGGERYLDFLRFAVFVNGESVEEN 2350
2351 ANVVVRLLIRKPECFGPALRGEGGSGLLATIEEAIRISEDPARDGPGVRR 2400
2401 DRRREHFGEEPPEENRVHLGHAIMSFYAALIDLLGRCAPEMHLIQAGKGE 2450
2451 ALRIRAILRSLVPLDDLVGIISLPLQIPTLGKDGALVQPKMSASFVPDHK 2500
2501 ASMVLFLDRVYGIENQDFLLHVLDVGFLPDMRAAASLDTATFSTTEMALA 2550
2551 LNRYLCLAVLPLITKCAPLFAGTEHRAIMVDSMLHTVYRLSRGRSLTKAQ 2600
2601 RDVIEECLMALCRYIRPSMLQHLLRRLVFDVPILNEFAKMPLKLLTNHYE 2650
2651 RCWKYYCLPTGWANFGVTSEEELHLTRKLFWGIFDSLAHKKYDPELYRMA 2700
2701 MPCLCAIAGALPPDYVDASYSSKAEKKATVDAEGNFDPRPVETLNVIIPE 2750
2751 KLDSFINKFAEYTHEKWAFDKIQNNWSYGENIDEELKTHPMLRPYKTFSE 2800
2801 KDKEIYRWPIKESLKAMIAWEWTIEKAREGEEEKTEKKKTRKISQSAQTY 2850
2851 DAREGYNPQPPDLSGVTLSRELQAMAEQLAENYHNTWGRKKKQELEAKGG 2900
2901 GTHPLLVPYDTLTAKEKARDREKAQELLKFLQMNGYAVTRGLKDMELDTS 2950
2951 SIEKRFAFGFLQQLLRWMDISQEFIAHLEAVVSSGRVEKSPHEQEIKFFA 3000
3001 KILLPLINQYFTNHCLYFLSTPAKVLGSGGHASNKEKEMITSLFCKLAAL 3050
3051 VRHRVSLFGTDAPAVVNCLHILARSLDARTVMKSGPEIVKAGLRSFFESA 3100
3101 SEDIEKMVENLRLGKVSQARTQVKGVGQNLTYTTVALLPVLTTLFQHIAQ 3150
3151 HQFGDDVILDDVQVSCYRTLCSIYSLGTTRNPYVEKLRPALGECLARLAA 3200
3201 AMPVAFLEPQLNEYNACSVYTTKSPRERAILGLPNSVEEMCPDIPVLERL 3250
3251 MADIGGLAESGARYTEMPHVIEITLPMLCSYLPRWWERGPEAPPPALPAG 3300
3301 APPPCTAVTSDHLNSLLGNILRIIVNNLGIDEASWMKRLAVFAQPIVSRA 3350
3351 RPELLHSHFIPTIGRLRKRAGKVVAEEEQLRLEAKAEAEEGELLVRDEFS 3400
3401 VLCRDLYALYPLLIRYVDNNRAHWLTEPNPSAEELFRMVGEIFIYWSKSH 3450
3451 NFKREEQNFVVQNEINNMSFLTADNKSKMAKSGGSDQERTKKKRLGDRYS 3500
3501 VQTSLIVATLKKMLPIGLNMCAPTDQELITLAKTRYALKDTDEEVREFLQ 3550
3551 NNLHLQGKVEGSPSLRWQMALYRGLPGREEDADDPEKIVRRVQEVSAVLY 3600
3601 HLEQMEHPYKSKKAVWHKLLSKQRRRAVVACFRMTPLYNLPTHRACNMFL 3650
3651 ESYKAAWILTEDHSFEDRMIDDLSKAGEQEEEEEEVEEKKPDPLHQLVLH 3700
3701 FSRTALTEKSKLDEDYLYMAYADIMAKSCHLEEGGENGEAQEEVEVSFEE 3750
3751 KEMEKQRLLYQQARLHNRGAAEMVLQMISACKGETGAMVSSTLKLGISIL 3800
3801 NGGNADVQQKMLDYLKDKKEVGFFQSIQALMQTCSVLDLNAFERQNKAEG 3850
3851 LGMVNEDGTVINRQNGEKVMADDEFTQDLFRFLQLLCEGHNNDFQNYLRT 3900
3901 QTGNTTTINIIICTVDYLLRLQESISDFYWYYSGKDVIEEQGKRNFSKAM 3950
3951 SVAKQVFNSLTEYIQGPCTGNQQSLAHSRLWDAVVGFLHVFAHMMMKLAQ 4000
4001 DSSQIELLKELLDLQKDMVVMLLSLLEGNVVNGMIARQMVDMLVESSSNV 4050
4051 EMILKFFDMFLKLKDIVGSEAFQDYVTDPRGLISKKDFQKAMDSQKQFTG 4100
4101 PEIQFLLSCSEADENEMIDCEEFANRFQEPARDIGFNVAVLLTNLSEHVP 4150
4151 HDPRLRNFLELAESILEYFRPYLGRIEIMGASRRIERIYFEISETNRAQW 4200
4201 EMPQVKESKRQFIFDVVNEGGESEKMELFVSFCEDTIFEMQIAAQISEPE 4250
4251 GEPEEDEDEGAGLAEAGAEGAEEGAVGPEGAAGTAAAGLTARLAAATSRA 4300
4301 LRGLSYRSLRRRVRRLRRLTAREAATALAALLWAALAHAGAAGAGAAAGA 4350
4351 LRLLWGSLFGGGLVEGAKKVTVTELLAGMPDPTGDEVHGEQPAGPGGEAD 4400
4401 GEGAGEGAGEAWEGAGDEEVAVQEAGPGGADGAVAVAEGGPFRPEGAGGL 4450
4451 GDMGDTTPAEPPTPEGSPIIKRKLGVDGEEEELPPEPEPEPEPEPEKADA 4500
4501 ENGEKEEVPKPPPEPPKKTAPPPPPPKKEEGGSGGLEFWGELEVQRVKFL 4550
4551 NYLSRNFYTLRFLALFLAFAINFILLFYKVSDSPPGEDDMEGSAAGDLSG 4600
4601 AGSGGGSGWGSGAGEEVEGDEDENMVYYFLEESTGYMEPALRCLSLLHTL 4650
4651 VAFLCIIGYNCLKVPLVIFKREKELARKLEFDGLYITEQPEDDDVKGQWD 4700
4701 RLVLNTPSFPSNYWDKFVKRKVLDKHGDIYGRERIAELLGMDLATLEITA 4750
4751 HNERKPEPPPGLLTWLMSIDVKYQIWKFGVIFTDNSFLYLGWYMVMSLLG 4800
4801 HYNNFFFAAHLLDIAMGVKTLRTILSSVTHNGKQLVMTVGLLAVVVYLYT 4850
4851 VVAFNFFRKFYNKSEDEDEPDMKCDDMMTCYLFHMYVGVRAGGGIGDEIE 4900
4901 DPAGDEYELYRVVFDITFFFFVIVILLAIIQGLIIDAFGELRDQQEQVRE 4950
4951 DMETKCFICGIGSDYFDTTPHRFETHTLEEHNLANYMFFLMYLINKDETE 5000
5001 HTGQESYVWKMYQERCWDFFPAGDCFRKQYEDQLS 5035
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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