 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9PU36 from www.uniprot.org...
The NucPred score for your sequence is 0.99 (see score help below)
1 LDTTHHPRQPGKPPDPGPGLSKSRTVDVLKTEQRAPGRSPSSISLRESKS 50
51 RTDFKEDQKPSMMPSFFSEANPLSAVTSVVNKFSPFDLISDSDAAHEEAG 100
101 RKQKVTQKEQGKPEEQRGLAKHPSQQQSPKLVQQQGPVKPTPQQTESSKP 150
151 VPQQQQPGEPKQGQKPGPSHPGDSKAEQVKQPPQPRGPQKSQLQQSEPTK 200
201 PGQQQTSAKTSAGPTKPLPQQPDSAKTSSQAPPPTKPSLQQSGSVKQPSQ 250
251 QPARQGGPVKPSAQQAGPPKQQPGSEKPTAQQTGPAKQPPQPGPGKTPLQ 300
301 QTGPVKQVPPQAGPTKPSSQTAGAAKSLAQQPGLTKPPGQQPGPEKPLQQ 350
351 KQASTTQPVESTPKKTFCPLCTTTELLLHTPEKANYNTCTQCHTVVCSLC 400
401 GFNPNPHITEIKEWLCLNCQMQRALGGDLASGHGPGPQLPPPKQKTPTPA 450
451 STAKPSPQLQPGQKKDASPKPDPSQQADSKKPVPQKKQPSMPGSPPVKSK 500
501 QTHAEPSDTGQQIDSTPKSDQVKPTQAEEKQNQPSIQKPTMDTVPTSAAP 550
551 GVKQDLADPQSPSTQQKVTDSPMPETTKPPADTHPAGDKPDSKPLPQVSR 600
601 QKSDPKLASQSGAKSDAKTQKPSEPAPVKDDPKKLQTKPAPKPDTKPAPK 650
651 GPQAGTGPRPTSAQPAPQPQQPQKTPEQSRRFSLNLGGITDAPKPQPTTP 700
701 QETVTGKLFGFGASIFSQASSLISTAGQPGSQTSGPAPPATKQPQPPSQP 750
751 PASQAPPKEAAQAQPPPKAAPTKKETKPLASEKLGPMASDSTLTTKGSDL 800
801 EKKPSLAKDSKHQTAEAKKPAELSEQEKASQPKVSCPLCKTGLNIGSKDP 850
851 PNFNTCTECKKVVCNLCGFNPMPHIVEVQEWLCLNCQTQRAMSGQLGDMG 900
901 KVPLPKLGPSQPVSKPPATPQKQPVPAVSHSPQKSSTPPTPAATKPKEEP 950
951 SVPKEVPKLQQGKLEKTLSADKIQQGIQKEDAKSKQGKLFKTPSADKIQR 1000
1001 VSQKEDSRLQQTKLTKTPSSDKILHGVQKEDIKFQEAKLAKIPSADKILH 1050
1051 RLQKEDPKLQQMKMAKALSADKIQPEAQKEDVQLQEVRLSKAVSADKIQH 1100
1101 GIQKDLNLQHVKIEKTSSVEKIQEAQKESKLQQDKLPKTLSEDKIPATVS 1150
1151 SDHKKLLSKSEEDKKPELLEKSTPHPKDKKEQITAETTGHITEQKVEVEA 1200
1201 PCDKLHEKKQEDVKKEDLTTGIPQMVSKPEKAEEEKTPVPVSRLPRSDHV 1250
1251 EAVREKIEKEDDKSDTSSSQQQKSPQGLSDTGYSSDGISSSLGEIPSHIP 1300
1301 SDEKDLPREPSQKDTISQESPPSPSDLAKLESTVLSILEAQASTLTDEKS 1350
1351 VKRKELYETYSEQTKDQHKTKPLPVTPESYSSDEEDLEAIQEGERTIAAD 1400
1401 SKGGASSQTDYKEEDGGNDTPARRQRYDSVEDSSESENSPVPRRKRRASV 1450
1451 GSSSSDEYKRDDSQGSGDEEDFIRKQIIEMSADEDASGSEDDEFIRNQLK 1500
1501 EISVTESQKKEEVKSKAKGTVGKHRRMARKSSAGYDEDAGRRHSWHDDDD 1550
1551 ETFDESPEPKYRETKSQDGEELAISGGGGLRRFKTIELNSTITSKYSETP 1600
1601 EQQKGILYFDEEPELEMESLTDSPEDRSRGEGSSSLHASSFTPGTSPTSV 1650
1651 SSLDEDSDSSPSHKKLGGESKQQRKARHRSHGPLLPTIEDSSEEEELREE 1700
1701 EELLKEQEKQRELEQQQRKSSSKKSKKDKDELRAQRRRERPKTPPSNLSP 1750
1751 IEDASPTEELRQAAEMEELHRSSCSEYSPSIESDPEGFEISPEKIIEVQK 1800
1801 VYKLPTAVSLYSPTDEKLIGALKEESGQKTLKSAEEVYEEMIHKTHKSKS 1850
1851 FQIASEKDEVFEKESLYGGMLIEDYIYESLIEDTYNGTVDTNLAMRQDES 1900
1901 NEYIQQRGKEKKIRASEQIYDEPQKITDLQEDYYSVEPLCSIVPQEDIVS 1950
1951 SSYIIPESHEIVVLDSTVTSTTEEKQLLDAEAAYEELMKKQRMQLTPGSS 2000
2001 PTQPTSDLAPTSDMKVSSIGEIADSTSLTSSTTSAISDVSSLSSIALSIP 2050
2051 DVKITQHFTAEEIEDEYLTDYAREIQEIISHETSMLTYSEVSEGAASILP 2100
2101 SDTASLTSSTSSVCTTDSSSPIDSATTGYVDTSDAVSKLVDSEDIIAQVP 2150
2151 FTSTEEYSEVSMPYESVAGATTKPAIASDMDTVHQAAVCLPETAPSVFTT 2200
2201 TVIKPKQYASDTITYDISTAEKDAARKMKSTVETGIIKIHHEDSHKELSL 2250
2251 DMTRINLTGATSEQPPLCVASVSVKEPASETPAVPTPRVVSKTSTVSMPS 2300
2301 SAPALTSKVFSLFRSSSLDSPAQPSPPSPPPPPPPPPPPLPPPILPKPAI 2350
2351 YPKKKSQIQAPMATAPTAVPLVTSVATLESAAVLKNHVVPVTKTYTPTPP 2400
2401 PVPPKPSSIPAGLVFSHRPTEVTKPPIAPKPAVPPLPIAVHKPAETQPKP 2450
2451 IGLSLTSSMTLNLVSSAEYKIASPTSPLSPHSNKSSPRLTKPSQETYVVI 2500
2501 TLPSEPGTPTEAITSQAVTSWPLEAPSKEQIPQPMQPIFTSSMKAVEIQS 2550
2551 MADQSMYITGALQTIPITTQSTFEKVPSSKSEAVTTEVAKTTASVVKRPV 2600
2601 PSVGLGSVTITIPPEPIYISDQPRYRENGRFHPLGDVIDLRTLTKVDIEM 2650
2651 RDSCMDLSAVSMDARRQMPTSDTSGRPVSTVQPAIINLSTACVADPSLSI 2700
2701 VTETVAVMTCTATVSYSASTDSLVDLGHAMTTPLQLTTSKHFEPAYRVTS 2750
2751 SQPFPVSRDEVPINLSLGTSAHAVTWAATKPVTVPPVSVTNGWTDLSTSQ 2800
2801 EPMEIGAVDLSTTKSHRTVVTMDETTSGIITTVIEDDEKPVDLTAGRRAV 2850
2851 CCDMVYKLPFGRSCTAQQPPTTLPEDRFGYRDDHYQYDRSGSYGYRGMGG 2900
2901 MKPSMSDTNLSEAGLFAYKSKNSFDYQVGATDAAVDLTSGRVTSGEVMDY 2950
2951 SSKTTGPYPETRQVISGIGISTPQYSQARMVSSLSSPFGAGSVLRSSNGV 3000
3001 VYSSVATPIPSTFAITTQPGSIFSTTVRDLPTLQTIDSVPSLSTLQQNQP 3050
3051 LPRSYSFLTTMAAEKDASTTLDIETGLPPLTLESIATEPTNLIPATASEV 3100
3101 YTDVIEDEVALIIAPEEGKQQQLDLERELLELEKIKQQRFAEELEWERQE 3150
3151 IQRFREQEKFMVQKKLEELQSMKHHLLFQQEEERQAQYMMRQETLAQQQL 3200
3201 QLEQFQQLQQQLHQQLEEQKIRQIYQYGYDPSGTGSPQTTTDQALLEGQY 3250
3251 ATAENGQFWPTDDATTTASGVLGIEISQSQTWYTVQSDGITQYIPRSGIL 3300
3301 SSVSEMSLKDIDVREEKQLKKRSSMPKLRGPYEELEESLEEEPRCYKKIV 3350
3351 DSGVQTDDEDGADRGYTNRRRRTKKSVDTSVQTDDEDQDEWDLSSRSGRK 3400
3401 PRVGKYSESTTEADKAKQFSKVSSIAVQTVAEISVQTEPVGTIRTPSIRA 3450
3451 RLDAKVEIIKHISAPEKTYKGESLGCQTETESDTQSPQYLSASSPQKDKK 3500
3501 RPTPLEIGYSSHLRPDSTLQVVPSPPKSPKVLYSPISPVSPSKVIESAFV 3550
3551 PYEKSITDDISPQKMLHPDIAKVPPSSPKAAKMMQRSMSDPKPLSPTAED 3600
3601 SSRAQFQYTEGFMTKGSSSITPSGTQKKVKRTLPNPPPEEATAGTQSPYT 3650
3651 SVGSVSRRRICRTTTMARAKILQDIDRELDLVERESAKLRKKQAELDEEE 3700
3701 KEIDAKLRYLEMGINRRKEALLKEREKRERAYLQGVAEERDYMSDSEVNN 3750
3751 TRSTRIETQHGLERPRTAPQTEFNQFMPPQTQPETQFAPATSPYGQYQYS 3800
3801 SPALPTQAPTQFTQQSHYQQQQPLYHQQVSPYQTQTAFQTGATMSFTPQA 3850
3851 QPPPTQQPSYQLSSQMMVIQPKPRQTPLYLEPKITTNYDVIRNQPLMIAP 3900
3901 VSTDNNYAVSQLGSKYTTLDLRIGLDERNSIASSPISSISADSFYADIDQ 3950
3951 HHTPRNYVLIDDIGELTKGTGALGSGFSLHEKDLTKTDRLLRTTEARRAQ 4000
4001 EVSDFLAPLQTSSRLHSYVKADEDPMEDPYELKLLKHQIKQEFRRGAESL 4050
4051 DHLAGLSQYYHPEGSFRHFPKSEKYSIGRLTLEKQAAKQLPAALLYQKQS 4100
4101 KHKKALIDPKLTKFSPIQESRDLEPDYSTYMTSSSTSSLGGITTRARLLQ 4150
4151 DDITFGLRKNITDQQKYMGAPLTSSIGAGLGAALGPTMRSTLQDEADKSY 4200
4201 SSGSRSRPSSRPSSVYGLDLSLKRDSSSSSLRLKAQEAEPLDVSFSHAAP 4250
4251 SGRTKPTSLPISQSRGRIPIVAQNSEEESPLSPVGQPMGMARAAAGPLPP 4300
4301 ISADTRDQFGSSHSLPEVQQHMREESRTRGYDRDIAFIMDDFQHAMSDSE 4350
4351 AYHLRREETDWFDKPRESRLENGHGLDRRLPEKLSHSRPPSQHQDQISCQ 4400
4401 INGKPLQYIFPHARLKLLRDPKDHTVSGNGLGIRVVGGKEIPGSSGEIGA 4450
4451 YIAKVLPGGNAEQTGKLIEGMQVLEWNGIPLTGKTYEEVQNIIIQQCGEA 4500
4501 EICVRLDLNMLSDSENPQHLELHEPVKAVDKAKSPGVDPKQLAAELQKVS 4550
4551 LQQAPLLASSGVEKSSHVHSGTTSATSSAVPSPGQPGSPSVSKKRHSSKP 4600
4601 AEATKSGSHPITGEIQLQINYDKHLGNLIIHILQARNLAPRDNNGYSDPF 4650
4651 VKVYLLPGRGQVMVVQNASAEYKRRTKYVQKSLNPEWNQTVIYKNISTEQ 4700
4701 LKKKTLEVTVWDYDRFSSNDFLGEVLIDLSSVSQLDNTPRWYPLKEQSEN 4750
4751 IDHGKSHSGQNSQQSPKPSVIKSRSHGIFPDPSKDMQVPTIEKSHSSPGS 4800
4801 SKSSSEGHLRSHGPSRSQSKTSVTQTHLEDAGAAIAAAEAAVQQLRLQPT 4850
4851 AHKSGQSNHARKQHRHSIAGVLPIQRTQSDNLPPPANDNKDQSQLALRKV 4900
4901 MSDGPVKPEGARSTNHRPAESSVSTGSSVSSFGSGYSMDSEGSSSATGEN 4950
4951 NLFPIPRIGKMSQNGQEPIKQSGVGLTDAEGKTQVMGEIKIALKKEMKTD 5000
5001 GEQLIVEILQCRNITYKFKSPDHLPDLYVKLYVVNVSTQKRVIKKKTRVC 5050
5051 RHDREPSFNETFRFSLSPAGHSLQILLVSNGGKFMKKTLIGEAYIWLDKV 5100
5101 DLRKRTVNWHKLLVSSTQTH 5120
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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