 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9VR91 from www.uniprot.org...
The NucPred score for your sequence is 0.65 (see score help below)
1 MFNRQASGGAGSSGQGAGSSQTASAAPVSAGVGVGGGGGASGAAAGAGSA 50
51 AGSGSGSGSGSAAPPSHSPDLYLRPLPFLDAKWLRADLIASLRNAADGAV 100
101 LWNHLIQDCELVSSPTAPLLNARGQLSYLGDDGKHYCGAQQLKCSCCQPE 150
151 YCGPLSACNCDGCRPLDSDTAIKKLTTQAAAQQAAHLSQATDMVLSGWLW 200
201 SQPPSQQARLDCQRSMISELQELALRAAGNCLSAQHLRQQLFIYERYFVA 250
251 LKRERERERKSTTSAQAVASVTTANTTIAATTANAAVESQPAEQQAEHGA 300
301 LGLARVATHAALNFSFAFLRRAWRSGEDTEMCSELLSEALASLQELPEAT 350
351 LFEAAVVSSLWLEVMERSIKFLRLVALGDPMGNRCTAPLNDRHTALCLLL 400
401 ELGVQKGTLAATLECVVLLLLLWEKDRAGNDNRDMPRKTGAPLQRILLRY 450
451 QKIGATAKGGGIAGGEPAPVASATETFLRFLSLPKSSAAIVDLRRAAVVI 500
501 ISHLDRMVQPLMPRCLLRGGQATAASSSSAPQQRIYALGWPSLSKDQQGF 550
551 SAEPTLSWSGESAGVPTLSCRFQIKQVACCETQMLILSQEGKLYTWRLAK 600
601 PEAEPLPMEEVAHDVFISIAGHCEGRHFLAIDSNHNAYSWGTGEDHRLGH 650
651 GDTHARAVPTKIAALEQHCVQSVYCGCSYSAAITCGGNLLTWGRGTYARL 700
701 GHGNSDDRSLPTLVVALSDHMVVDVALGSGDAHSLALTSEGLVFAWGDGD 750
751 YGKLGNGNCNGSLQPILVESLPRVQRVFAGSQFSVALSSEGQLYTWGKAT 800
801 CLGHQLVERSVQGCSVPRLVSSLQHKRIVDVAVSVAHCLALSSSGEVFGW 850
851 GRNDSQQICPASVSSEPLLRTPILVSLPTFPASGIACTSAQSLVWTQSSH 900
901 QGVPRRAPFVVDLGEPTFRLLDQLLGMCSSQDNRQTPNQESECIAVACLN 950
951 LFRLQLLALIANGVEPRQVGLASGSRLLCSLKTRILGLAGGSQVLRTIQV 1000
1001 AAQQALQDGWSVLLPTAAERAQTLTSLLPSEPGQASSAGHRFMTDLLVSS 1050
1051 LMAEGGLESALQHAIRLESSSCSADCGDGVHLPLLQLITRLLSNNAALSQ 1100
1101 TRLSPTLGKQQEKEEEEREQQHQEPSTSPSLSLLHRFQRLLLSHIHQAQP 1150
1151 EEETTGAEALLLQYMHALIPACVATLQKAHELALQCREPGENSFGQMVGH 1200
1201 LGRVLQADISDALLNELLVGLLLLKRDRPQCLGGLRWARLFLPLLRVLDR 1250
1251 LNRALGEGELRDGDDMGWPGIICRGGPKGGPPPADPETHYVRRADMENLL 1300
1301 LDGSRCIILAGYVCDLSGYNCESETLRSVLDSGLGKDLTAEMSSQVHRTA 1350
1351 MEHILEHHKLGKYMVQASTEEKSSAPGPSRLTHFSSECALAQLLGLVANL 1400
1401 MCSGPALQPAELQCRQLDKSSLLSGGLQLLQPSNPFDEEKGEARSSHSCH 1450
1451 STAGNTPTELPPPLPMQQQLAPGRGKSQLQLRADAFISGLAEARVSEPPV 1500
1501 AAWLALTERYCKAHNLMWHQEFATEHPVQELERLLSAVLIRHQYLGGLVL 1550
1551 NALETEVPPPRQLGEIIRLVHQAKWSVVRTRQQLNRSYKEVCAPILERLR 1600
1601 FLLYEVRPAISPQQRGLRRLPILQRPPRFKMLVRRLLQELRSSRQPAKPE 1650
1651 DLLNASIQQEQEKKPQSMPKQELEEQEEEETLLRRLNERQIHGEGELDPA 1700
1701 LMQDIVDFALQDSCDVETARRAMYCQMQRYQLRLAGLQIVQQLLELHGLL 1750
1751 DAAQYSLLNGFLGLHLKSTSSGGGSTGSGSSLHVLGQLNMISAYQKARLL 1800
1801 LAQSRVLDWAVRELRRLVNQEQQGHARGKDSTNLGTYVLLKRLPRARFLL 1850
1851 SVFGLLAKELGPNELGFLINSGLLGTVLGLLAQTGGEGATGGQVHGELSI 1900
1901 LYEDSVLKQKSSKAQLSGPDLAKLMKIGTRIVRGADWKWGDQDGNPPGEG 1950
1951 RIISEVGEDGWVRVEWYTGATNSYRMGKEGQYDLQLADSALNVASPTEPE 2000
2001 REDVSGSEASPTSDSHPSKLLRHCAAKLLQILAVGTGLHGAQLDKDALRG 2050
2051 MTSMFRTIIYPKPSMSNISYALGWLNLGFIRAISGDCPRLCLELSTPGWL 2100
2101 SHYLSLLEQPAGNEAGVYRQLHCLRLLQLILAQWGAEEEPRMPALVHQLF 2150
2151 ATLGRIALHCPGDASLLPTAEGKARVLLTASHSGSVAEELVALLRRLHTL 2200
2201 PSWNPVINSFLAQKLCVAAELLAEQSHSTALDSEQVFVLGVLGAMGGHDL 2250
2251 RPRVGLHCFHEGSHMVIASFTPKGRCLLAPGGVGSGVGFVKVQLPAVMPH 2300
2301 LDHTVFSLSRLPMNEMLLNAWTVLLYGPAPELRELPSSADGRLDLALLRA 2350
2351 QQLQMAVLHTNGVLYRHQVALRRILKQRAPGSIYASPDEPDRSDAESQQP 2400
2401 GEQDQQLSSGSGQEPQLLIQCILLRATQASPVKACYSYMDLATAALNCIQ 2450
2451 SLATQAHQELSEGGGVPPNGRALSSPPQPTMVHGVPVYNVARKEQKPSEQ 2500
2501 VEQKSKWPAAATDAQLIGQIMEMGFTRRTVELALKQLSLQAEIMPTPEQI 2550
2551 VQWILEHPDVCANTIEEDTLPLASSASSHDPEADSDNECPSSNSTTSSST 2600
2601 SSDTVEGQPMAVSGPAPPVKFESRKDFQTADLYALYVRGLVRPGMTVRCC 2650
2651 RDFEEIKQGDMGTVLIVDTEGLHDLNVQVDWRNHGSTYWVCFVHIELVEA 2700
2701 AQTHHQPRPPPIAVGARVRLRTSSLRYGMLCPLRLGRSQGSSAIGVVSSV 2750
2751 RSKQLTVDFPDQPAWQGHINEVELVASQPTSATLPSLGDSCSQMPPSDLI 2800
2801 EDWSRCIRSLTVSSNEAAAKHLLNGSNQPWQSCSSGPCRHWIRLELHDRI 2850
2851 LVHSLTLKVSPEDHSHMPSLLEIRVGDCVDSLKEYTWIPVPAGASRVLLM 2900
2901 QQVPTYYPWVEVVVKQCQNNGIQCKIHGIKFVGRRQQPDLQHILANAQFL 2950
2951 ASEYSAGVGPGSTAGAGAVSTSHEEAAAAPEQDLPCTVMVWGLNDKEQLG 3000
3001 GLKGSKVKVPTFSQTISRLRPIHIAGGSKSLFIVSQDGKVYACGEGTNGR 3050
3051 LGLGVTHNVPLPHQLPVLRQYVVKKVAVHSGGKHALALTLDGKVFSWGEG 3100
3101 EDGKLGHGNRTTLDKPRLVEALRAKKIRDVACGSSHSAAISSQGELYTWG 3150
3151 LGEYGRLGHGDNTTQLKPKLVTALAGRRVVQVACGSRDAQTLALTEDGAV 3200
3201 FSWGDGDFGKLGRGGSEGSDTPHEIERLSGIGVVQIECGAQFSLALTRAG 3250
3251 EVWTWGKGDYYRLGHGGDQHVRKPQPIGGLRGRRVIHVAVGALHCLAVTD 3300
3301 AGQVYAWGDNDHGQQGSGNTFVNKKPALVIGLDAVFVNRVACGSSHSIAW 3350
3351 GLPNASSDEEKRGPVPFSSTRDPLGGSSLGIYEAETMQTLKQEAKPLNQS 3400
3401 SLSESLALETPAARQAALGHVLRAMSILQARQLIVAALTSHSKVNFKERG 3450
3451 AVGGEEDHLIGGPIMGAPLQLAETIAQGGGEAPADATDAGLQEHSPEAAV 3500
3501 DALTGGMSGGANTLPPLSAGPLSAFQSLTGSLSMSGSLSSSALPQHKHSR 3550
3551 MSASAMSVMAATMTQQEEMLSHISHCHGLDDFGGLLGEPEAKSLVELLKL 3600
3601 AVCGRCGPPSTSQTIADTLISLGAGTPAVAAMLLETCITELEDLCTSRHC 3650
3651 LGKLPKPVMQESSHPYVDNVNVTGVVRIPGAEMLRLEFDSQCSTEKRNDP 3700
3701 LVIMDGTGRVLAMRSGREFAHWAPEIRVLGDELRWKFSSDSSVNGWGWRF 3750
3751 WVHAIMPAATLGESGSDRAVLSQPSMALVMSLLDSRLAPRQPSVLLRLAS 3800
3801 ALAACSQLGALTTAQRIWSLRKLHAVLLLEQAPRPQDPSLSTLLQPLIPE 3850
3851 LLRQYEYEEPQVRGGIHLMHSDYFKTLAALACDMQLDAALPATSSSSSSS 3900
3901 AAPGAISSTGDVHKWAWFKRYCIAVRVAQSLIRRTELPRAFCLEVRKKFA 3950
3951 EMLPSSSSNSNANPGCQSPGASMLNSTTSLSSSTVSNVSPPPGITGEQPD 4000
4001 LHCHAHQLESTSTLLHEDHTLFQAPHDAQLLQWLNRRPDDWALSWGGAST 4050
4051 IYGWGHNHRGQLGGLEGSRIKTPTPCEALSLLRPVQLAGGEQSLFAVTPD 4100
4101 GKLFATGYGSGGRLGVGGSDSWAIPTLLGSLQHVFVKKVAVNSGGKHCLA 4150
4151 LTTEGEVYAWGEGEDGKLGHGNRMSYDRPKLVEHLNGMSVADIACGSAHS 4200
4201 AAITASGHVLTWGKGRYGRLGHGDSEDQLRPKLVEALLGYRAIDIACGSG 4250
4251 DAQTLCITDDDNVWSWGDGDYGKLGRGGSDGCKLPYKIESLAGLGVVKVE 4300
4301 CGSQFSVALTKSGAVYTWGKGDFHRLGHGSVDHVRRPKKVAALQGKKIIS 4350
4351 IATGSLHCVACSDSGEVYTWGDNDEGQLGDGTVTAIQRPRLVAALQGKHI 4400
4401 VKVTCGSAHTLALSTSQLSERLRPLPNPPLEYDLVRDLAPEALHARLILL 4450
4451 HHFSELVCPCLAMLPISGDLSLGALKDVLVYNIKEAAFRKVIQTTMVRDK 4500
4501 QHGPVIELNRIQVKRSRNRCNGLAGIDGMKSVFGQMVQKLPLLTQEALAL 4550
4551 PHRVWKVKFVGESVDDCGGGYSESIAEMCDELQNGSVPLLINTPNGRGEA 4600
4601 GANRDCFLLDPTLSSVLQMNMFRFLGVLMGIAVRTGSPLSINLAEPVWRQ 4650
4651 LTGEVLRPTDLTEVDRDYVAGLLCIRNMDDDPKLFTALELPFSTSSARGH 4700
4701 EVPLSTRYTHISPRNRAEYVRLALGFRLHEFDEQVKAVRDGMSKVIPVPL 4750
4751 LSLFSAAELQAMVCGSPDIPLGLLKSVATYKGFDPSSALVTWFWEVMEEF 4800
4801 TNQERSLFLRFVWGRTRLPRTIADFRGRDFVLQVLEKNPPDHFLPESYTC 4850
4851 FFLLKMPRYSCKAVLLEKLKYAIHFCKSIDTDEYARVAMGEPTEATGSED 4900
4901 NSDLESVASHEG 4912
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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