 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O01761 from www.uniprot.org...
The NucPred score for your sequence is 0.57 (see score help below)
1 MASRRQKQFDRKYSSYRKFTATEDVNYSTHSSRSSYRSESLTSRTDGRGR 50
51 STSSEIIAGSESRSYPVYIAIQDYTPDKEDVEAIPLEQGQIVEVLDKKNS 100
101 VRWLVRTKARPPRSGWVPGSYFETPTEFYKQRRRTREIENVSLSDEQAAL 150
151 VKRDQVYHELLRSEEEFVSSLRTCVDDYIKVLDDPEVPEAVKKNREELTL 200
201 NIPELYNFHANVMLKGLNYYSDDPGKVGQTFVRLEKDFESHVEFYKQYAD 250
251 TLKLLEEPEIKRFFEGLSAKNDAGASSFVDHVKEIADRMVQYQNYFKEFV 300
301 KYSARAHGSSKSIQKALELVTTIPQRVHDLEFTNNLKQHPGDTGKLGRII 350
351 RHDAFQVWEGDEPPKLRYVFLFRNKIMFTEQDASTSPPSYTHYSSIRLDK 400
401 YNIRQHTTDEDTIVLQPQEPGLPSFRIKPKDFETSEYVRKAWLRDIAEEQ 450
451 EKYAAERDAISMTATSEMTASSVDFDMNASDQQSEFSEWSGSRKSSLFPG 500
501 PEEGGPPRKKVKSPPVISPTGSSTSIYSGGSSSIDWTTTGTTLEMQGTRV 550
551 TRTQYGFRTLQESSAKMCLKVTGYPLPDITWYKDDVQLHEDERHTFYSDE 600
601 DGFFAMTIDPVQVTDTGRYTCMATNEYGQASTSAFFRVLKVEKEAAPPAF 650
651 VTKLRDKECKEGDVIDFECEVEGWPEPELVWLVDDQPLRPSHDFRLQYDG 700
701 QTAKLEIRDAQPDDTGVYTVKIQNEFGSIESKAELFVQADPDKNHVAPEF 750
751 QATIEYVECDEGEEVRFKSVITGDPNPEIIWFINGKPLSESEKVKFISED 800
801 GICILTIKDVTRHFDGMVTCQGSNRLGSASCDGRLKVRVPPAPPTFNKPL 850
851 EDKTVQEKSTVVFEVDVSGWPEPTLTFTLCGKELKNGEEGVEIVGHDGFY 900
901 RISIPNTSMDKHDGEIVAKAQNEHGTAESRARLTVEQEEEESRSAPTFLK 950
951 DIEDQTVKTGEFAVFETTVRGNPNPEVTWFINGHKMDQGSPGVKIEAHNH 1000
1001 DHKLTIDSAQYAGTVLCRAENAVGRFETKARLVVLAPEKQKKPPKFVEIL 1050
1051 VDKTETVDNTVVFEVRVEGEPKPTVTWYLKGEELKQSDRVEIREFDGSIK 1100
1101 ISIKNIKIEDAGEIRAVATNSEGSDETKAKLTVQKKPFAPEFDLRPVSLT 1150
1151 VEKGSEAVFSAHAFGIPLPTYEWSVNGRKVRDGQEGARVTRDESTVDGAS 1200
1201 ILTIDTATYYSEVNHLTISVVAENTLGAEETGAQLTIEPKKESVVVEKQD 1250
1251 LSSSEVQKEIAQQVKEASPEATTTITMETSLTSTKTTTMSTTEVTSTVGG 1300
1301 VTVETKESESESATTVIGGGSGGVTEGSISVSKIEVVSKTDSQTDVREGT 1350
1351 PKRRVSFAEEELPKEVIDSDRKKKKSPSPDKKEKSPEKTEEKPASPTKKT 1400
1401 GEEVKSPKEKSPASPTKKEKSPAAEEVKSPTKKEKSPSSPTKKEKSPSSP 1450
1451 TKKTGDEVKEKSPPKSPTKKEKSPEKPEDVKSPVKKEKSPDATNIVEVSS 1500
1501 ETTIEKTETTMTTEMTHESEESRTSVKKEKTPEKVDEKPKSPTKKDKSPE 1550
1551 KSITEEIKSPVKKEKSPEKVEEKPASPTKKEKSPEKPASPTKKSENEVKS 1600
1601 PTKKEKSPEKSVVEELKSPKEKSPEKADDKPKSPTKKEKSPEKSATEDVK 1650
1651 SPTKKEKSPEKVEEKPTSPTKKESSPTKKTDDEVKSPTKKEKSPQTVEEK 1700
1701 PASPTKKEKSPEKSVVEEVKSPKEKSPEKAEEKPKSPTKKEKSPEKSAAE 1750
1751 EVKSPTKKEKSPEKSAEEKPKSPTKKESSPVKMADDEVKSPTKKEKSPEK 1800
1801 VEEKPASPTKKEKTPEKSAAEELKSPTKKEKSPSSPTKKTGDESKEKSPE 1850
1851 KPEEKPKSPTPKKSPPGSPKKKKSKSPEAEKPPAPKLTRDLKLQTVNKTD 1900
1901 LAHFEVVVEHATECKWFLDGKEITTAQGVTVSKDDQFEFRCSIDTTMFGS 1950
1951 GTVSVVASNAAGSVETKTELKVLETPKETKKPEFTDKLRDMEVTKGDTVQ 2000
2001 MDVIALHSPLYKWYQNGNLLEDGKNGVTIKNEENKSSLIIPNAQDSGKIT 2050
2051 VEASNEVGSSESSAQLTVNPPSTTPIVVDGPKSVTIKETETAEFKATISG 2100
2101 FPAPTVKWTINEKIVEESRTITTIKTEDVYTLKISNAKIEQTGTVKVTAQ 2150
2151 NSAGQDSKQADLKVEPNVKAPKFKSQLTDKVADEGEPLRWNLELDGPSPG 2200
2201 TEVSWLLNGQPLTKSDTVQVVDHGDGTYHVTIAEAKPEMSGTLTAKAKNA 2250
2251 AGECETSAKVTVNGGNKKPEFVQAPQNHETTLEESVKFSAIVTGKPMPNV 2300
2301 TWYLNNKKLIQSEEVKVKYVHETGKTSIRIQKPLMEHNGTIRVEAENVSG 2350
2351 KVQATAQLKVDKKTEVPKFTTNMDDRQVKEGEDVKFTANVEGYPEPSVAW 2400
2401 TLNGEPVSKHPNITVTDKDGEHTIEISAVTPEQAGELSCEATNPVGSKKR 2450
2451 DVQLAVKKVGDAPTFAKNLEDRLITEGELTLMDAKLNIVKPKPKITWLKD 2500
2501 GVEITSDGHYKIVEEEDGSLKLSILQTKLEDKGRITIKAESEFGVAECSA 2550
2551 SLGVVKGRPMAKPAFQSDIAPINLTEGDTLECKLLITGDPTPFVKWYIGT 2600
2601 QLVCATEDTEISNANGVYTMKIHGVTADMTGKIKCVAYNKAGEVSTEGPL 2650
2651 KVVAPIPVEFETSLCDATCREGDTLKLRAVLLGEPEPVVSWYVNGKKLEE 2700
2701 SQNIKIHSEKGTYTVTIKDITCDYSGQVVCEAINEYGKATSEATLLVLPR 2750
2751 GEPPDFLEWLSNVRARTGTKVVHKVVFTGDPKPSLTWYINNKEILNSDLY 2800
2801 TIVTDDKTSTLTINSFNPDVHVGEIICKAENDAGEVSCTANMITYTSDMF 2850
2851 SESESEAQAEEFVGDDLTEDESLREEMHRTPTPVMAPKFITKIKDTKAKK 2900
2901 GHSAVFECVVPDTKGVCCKWLKDGKEIELIARIRVQTRTGPEGHITQELV 2950
2951 LDNVTPEDAGKYTCIVENTAGKDTCEATLTVIESLEKKSEKKAPEFIVAL 3000
3001 QDKTTKTSEKVVLECKVIGEPKPKVSWLHDNKTITQESITVESVEGVERV 3050
3051 TITSSELSHQGKYTCIAENTEGTSKTEAFLTVQGEAPVFTKELQNKELSI 3100
3101 GEKLVLSCSVKGSPQPHVDFYSFSETTKVETKITSSSRIAIEHDQTNTHW 3150
3151 RMVISQITKEDIVSYKAIATNSIGTATSTSKITTKVEAPVFEQGLKKTSV 3200
3201 KEKEEIKMEVKVGGSAPDVEWFKDDKPVSEDGNHEMKKNPETGVFTLVVK 3250
3251 QAATTDAGKYTAKASNPAGTAESSAEAEVTQSLEKPTFVRELVTTEVKIN 3300
3301 ETATLSVTVKGVPDPSVEWLKDGQPVQTDSSHVIAKVEGSGSYSITIKDA 3350
3351 RLEDSGKYACRATNPAGEAKTEANFAVVKNLVPPEFVEKLSPLEVKEKES 3400
3401 TTLSVKVVGTPEPSVEWFKDDTPISIDNVHVIQKQTAVGSFSLTINDARQ 3450
3451 GDVGIYSCRARNEAGEALTTANFGIIRDSIPPEFTQKLRPLEVREQETLD 3500
3501 LKVTVIGTPVPNVEWFKDDKPINIDNSHIFAKDEGSGHHTLTIKQARGED 3550
3551 VGVYTCKATNEAGEAKTTANMAVQEEIEAPLFVQGLKPYEVEQGKPAELV 3600
3601 VRVEGKPEPEVKWFKDGVPIAIDNQHVIEKKGENGSHTLVIKDTNNADFG 3650
3651 KYTCQATNKAGKDETVGELKIPKYSFEKQTAEEVKPLFIEPLKETFAVEG 3700
3701 DTVVLECKVNKESHPQIKFFKNDQPVEIGQHMQLEVLEDGNIKLTIQNAK 3750
3751 KEDVGAYRCEAVNVAGKANTNADLKIQFAAKVEEHVTDESGQLEEIGQFE 3800
3801 TVGDTASSKTDTGRGAPEFVELLRSCTVTEKQQAILKCKVKGEPRPKIKW 3850
3851 TKEGKEVEMSARVRAEHKDDGTLTLTFDNVTQADAGEYRCEAENEYGSAW 3900
3901 TEGPIIVTLEGAPKIDGEAPDFLQPVKPAVVTVGETAVLEGKISGKPKPS 3950
3951 VKWYKNGEELKPSDRVKIENLDDGTQRLTVTNAKLDDMDEYRCEASNEFG 4000
4001 DVWSDVTLTVKEPAQVAPGFFKELSAIQVKETETAKFECKVSGTKPDVKW 4050
4051 FKDGTPLKEDKRVHFESTDDGTQRLVIEDSKTDDQGNYRIEVSNDAGVAN 4100
4101 SKVPLTVVPSETLKIKKGLTDVNVTQGTKILLSVEVEGKPKTVKWYKGTE 4150
4151 TVTSSQTTKIVQVTESEYKLEIESAEMSDTGAYRVVLSTDSFSVESSATV 4200
4201 TVTKAAEKISLPSFKKGLADQSVPKGTPLVLEVEIEGKPKDVKWYKNGDE 4250
4251 IKDGKVEDLGNGKYRLTIPDFQEKDVGEYSVTAANEAGEIESKAKVNVSA 4300
4301 KPEIVSGLVPTTVKQGETATFNVKVKGPVKGVKWYKNGKEIPDAKTKDNG 4350
4351 DGSYSLEIPNAQVEDAADYKVVVSNDAGDADSSAALTVKLADDGKDKVKP 4400
4401 EIVSGLIPTTVKQGETATFNVKVKGPVKQVKWYKNGKEIPNAKAKDNGDG 4450
4451 SYSLEIPNAQLDDTADYKVVVSNDAGDADSSAALTVKLPGIAIVKGLEDA 4500
4501 EVPKGKKAVLQVETNKKPKEIKWYKNGKEITPSDKAQPGSDGDNKPQLVI 4550
4551 PDAGDDDAAEYKVVLTDEDGNTADSSCALTVKLPAKEPKIIKGLEDQVVS 4600
4601 IGSPIKLEIETSGSPKTVKWYKNGKELPGAAAKTIKIQKIDDNKYVLEIP 4650
4651 SSVVEDTGDYKVEVANEAGSANSSGKITVEPKITFLKPLKDQSITEGENA 4700
4701 EFSVETNTKPRIVKWYKNGQEIKPNSRFIIEQKTDTKYQLVIKNAVRDDA 4750
4751 DTYKIVLENTAGEAESSAQLTVKKAKAGLCKIVKGLEDQVVAKGAKMVFE 4800
4801 VKIQGEPEDVRWLRDANVISAGANAIIEKIDDTTYRLIIPSADLKDAGEY 4850
4851 TVEVINESGKAKSDAKGEVDEKPEIVRGLENIEIPEGDDDVFKVEVSAPV 4900
4901 RQVKWYKNDQEIKPNSHLEAKKIGPKKYELAINRAQLDDGADYKVVLSNA 4950
4951 AGDCDSSAALTVVKPNVLKIVDGLKDVDVEEPQPVELKVKVEGIPKVIKW 5000
5001 YKNGQELKPDADGFKFEEKPESGEFSLTIPSSKKSDGGAYRVVLGNDKGE 5050
5051 VYSGSVVHVKSAKSSEPTSGANFLSPLKDTEVEEGDMLTLQCTIAGEPFP 5100
5101 EVIWEKDGVVLQKDDRITMRVALDGTATLRIRSAKKSDIGQYRVTAKNEA 5150
5151 GSATSDCKVTVTEQGEQPSKPKFVIPLKTGAALPGDKKEFNVKVRGLPKP 5200
5201 TLQWFLNGIPIKFDDRITLDDMADGNYCLTIRDVREEDFGTLKCIAKNEN 5250
5251 GTDETVCEFQQGAGHDDGSRDDLRYPPRFNVPLWDRRIPVGDPMFIECHV 5300
5301 DANPTAEVEWFKDGKKIEHTAHTEIRNTVDGACRIKIIPFEESDIGVYMC 5350
5351 VAVNELGQAETQATYQVEILEHVEEEKRREYAPKINPPLEDKTVNGGQPI 5400
5401 RLSCKVDAIPRASVVWYKDGLPLRADSRTSIQYEEDGTATLAINDSTEED 5450
5451 IGAYRCVATNAHGTINTSCSVNVKVPKQEVKKEGEEPFFTKGLVDLWADR 5500
5501 GDSFTLKCAVTGDPFPEIKWYRNGQLLRNGPRTVIETSPDGSCSLTVNES 5550
5551 TMSDEGIYRCEAENAHGKAKTQATAHVQMALGKTEKPKMDEGKPPKFILE 5600
5601 LSDMSVSLGNVIDLECKVTGLPNPSVKWSKDGGPLIEDSRFEWSNEASKG 5650
5651 VYQLRIKNATVHDEGTYRCVATNENGSATTKSFVRMDDGLGSGVVTASQP 5700
5701 PRFTLKMGDVRTTEGQPLKLECKVDASPLPEMVWYKDGAIVTPSDRIQIS 5750
5751 LSPDGVATLLIPSCVYDDDGIYRVIATNPSGTAQDKGTATVKKLPRDSGA 5800
5801 RRSADRDVFDANKAPKLMEPLENIRIPEKQSFRLRCKFSGDPKPTIKWFK 5850
5851 DGERVFPYGRLQLIESPDGVCELVVDSATRQDAGGYRCVAENTYGSARTS 5900
5901 CDVNVIRGDRKPRDIDSSIREGKAPGFTTPLTIRRAKPGDSVTFECLPFG 5950
5951 NPFPSIKWLKDGLELFSDEKIKMEAAADGTQRLILSDVTFLSEGYFRCVA 6000
6001 TNEHGTASTKAELVIEGDRTIGSRPLPEVNGEPEECKPRIRRGLYNMSIH 6050
6051 EGNVVEMIVCATGIPTPTVKWYKDGQEIVGDGPDGKRVIFTDERGIHHLV 6100
6101 IVNASPDDEGEYSLEATNKLGSAKTEGSLNIIRPRHIADADERGGMPFPP 6150
6151 GFVRQLKNKHVFNHMPTIFDCLVVGHPAPEVEWFHNGKKIVPGGRIKIQS 6200
6201 CGGGSHALIILDTTLEDAGEYVATAKNSHGSASSSAVLDVTVPFLDSIKF 6250
6251 NGEIDVTPYLTEEYGFKKLNTASLPTPPDRGPFIKEVTGHYLTLSWIPTK 6300
6301 RAPPRYPQVTYVIEIRELPEKQWSLLEYNIPEPVCKVRNLELGKSYQFRV 6350
6351 RAENIYGISDPSPASPPSRLMAPPQPVFDRRTNKVIPLLDPYAEKALDMR 6400
6401 YSEQYACAPWFSPGVVEKRYCAENDTLTIVLNVSGFPDPDIKWKFRGWDI 6450
6451 DTSSPTSKCKVYTYGGSETTLAITGFSKENVGQYQCFAKNDYGDAQQNIM 6500
6501 VDLATRPNFIQPLVNKTFSSAQPMRMDVRVDGEPFPELKWMKEWRPIVES 6550
6551 SRIKFVQDGPYLCSLIINDPMWRDSGIYSCVAVNDAGQATTSCTVTVEAE 6600
6601 GDYNDVELPRRRVTIESRRVRELYEISEKDEKLAAEGAPFRVKEKATGRE 6650
6651 FLAQLRPIDDALMRHVDIHNSLDHPGIVQMHRVLRDEKLALVVFDNANST 6700
6701 IDGLSSLAHPGVEIAEPKGVNRETCVRVFVRQLLLALKHMHDLRIAHLDL 6750
6751 RPETILLQDDKLKLADFGQARRLLRGLITGEIKGSPEFVSPEIVRSYPLT 6800
6801 LATDMWSTGVLTYVLLTGLSPFHGDNDNETLANVDSCQFDSSPLGNFSYD 6850
6851 AGDFVKKLLTEIPVSRLTVDEALDHPWINDEKLKTEPLSADTLREFKYQH 6900
6901 KWLERRVFVQQTPSEQILEAILGPATAQAQQNAPVAPEGRRPAEIYDYLR 6950
6951 IQPKKPPPTVEYVPQPRKEHPPFIDEFGQLIDGDAFDRPEGTGFEGPHRQ 7000
7001 PPQIPPQPQRPNQAAHDSRRHEQQPQHQGQPQRIPVDQYGRPLVDPRYLN 7050
7051 DPSHRPSSLDDAPFYVDKYGNPVHFDKYGRPMAPQNLEKRKLIPQDKGET 7100
7101 PSHSKKEKTQHPVATPILASPGGDQQQQKIPMRMIRGERREIEEEIANRI 7150
7151 LSDISEEGSIAGSLASLEDFEIPKDFQVEASEPSTPTLTPEVTIRETIPK 7200
7201 PTPSPTSPQKSPVPQPQGLLIPAKVTYSDSILAGLPAADKKVLEDAENDP 7250
7251 SIPVGAPLFLEGLHGSDLTIDTTSASGLIKVTSPAINLSPNPKSPRRSTP 7300
7301 GTKSPVVLSPRQEHSMEVLIATKRGKPGFLPPGELAEDIDDEDAFMDDRK 7350
7351 KQVKPKDHDGENDFKDEKERLEKDKNRRTVNLDDLDKYRPSAFYKDDSDF 7400
7401 GHPGYDIDATPWDSHYQIGPDTYLMAARGAAFNSRVRNYREELFGMGAPT 7450
7451 VKQGFLGVRNRDITVRERRRYTDILRETTQGLEPKSHEQSTALLQKAPSA 7500
7501 TAIERIKADIEKVTPCATKKNDDGTFAPIFTARLRDVYLRKNQPAIFECA 7550
7551 VSASPAPKVTWDFQGKILESNDRVTIEQDNNVARLILNHAAPYDLGEYVC 7600
7601 TAINEYGTDKSSCRLISGETPSRPGRPEAELSSDTEIFIQWEAPEGPTYL 7650
7651 EGITYRLEYRVAGPNDHGDPWITVSEKIDDESVIVKHLSPLGIYQFRVTA 7700
7701 QNGFGLGLPSLSSRIVQTHGKGAPKLQIDVLKSEIRLNVVSMPQKSTNQL 7750
7751 GGISEESEEDSEARTANEDMKSNLQLQTDDPTGRFQIGGLKFKGRFSVIR 7800
7801 DAVDSTTEGHAHCAVKIRHPSSEAISEYESLRDGQHENVQRLIAAFNNSN 7850
7851 FLYLLSERLYEDVFSRFVFNDYYTEEQVALTMRQVTSALHFLHFKGIAHL 7900
7901 DVNPHNIMFQSKRSWVVKLVDFGRAQKVSGAVKPVDFDTKWASPEFHIPE 7950
7951 TPVTVQSDMWGMGVVTFCLLAGFHPFTSEYDREEEIKENVINVKCDPNLI 8000
8001 PVNASQECLSFATWALKKSPVRRMRTDEALSHKFLSSDPSMVRRRESIKY 8050
8051 SASRLRKLAAMIRQPTFSQPISEELESKYGK 8081
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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