 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O14686 from www.uniprot.org...
The NucPred score for your sequence is 0.96 (see score help below)
1 MDSQKLAGEDKDSEPAADGPAASEDPSATESDLPNPHVGEVSVLSSGSPR 50
51 LQETPQDCSGGPVRRCALCNCGEPSLHGQRELRRFELPFDWPRCPVVSPG 100
101 GSPGPNEAVLPSEDLSQIGFPEGLTPAHLGEPGGSCWAHHWCAAWSAGVW 150
151 GQEGPELCGVDKAIFSGISQRCSHCTRLGASIPCRSPGCPRLYHFPCATA 200
201 SGSFLSMKTLQLLCPEHSEGAAYLEEARCAVCEGPGELCDLFFCTSCGHH 250
251 YHGACLDTALTARKRAGWQCPECKVCQACRKPGNDSKMLVCETCDKGYHT 300
301 FCLKPPMEELPAHSWKCKACRVCRACGAGSAELNPNSEWFENYSLCHRCH 350
351 KAQGGQTIRSVAEQHTPVCSRFSPPEPGDTPTDEPDALYVACQGQPKGGH 400
401 VTSMQPKEPGPLQCEAKPLGKAGVQLEPQLEAPLNEEMPLLPPPEESPLS 450
451 PPPEESPTSPPPEASRLSPPPEELPASPLPEALHLSRPLEESPLSPPPEE 500
501 SPLSPPPESSPFSPLEESPLSPPEESPPSPALETPLSPPPEASPLSPPFE 550
551 ESPLSPPPEELPTSPPPEASRLSPPPEESPMSPPPEESPMSPPPEASRLF 600
601 PPFEESPLSPPPEESPLSPPPEASRLSPPPEDSPMSPPPEESPMSPPPEV 650
651 SRLSPLPVVSRLSPPPEESPLSPPPEESPTSPPPEASRLSPPPEDSPTSP 700
701 PPEDSPASPPPEDSLMSLPLEESPLLPLPEEPQLCPRSEGPHLSPRPEEP 750
751 HLSPRPEEPHLSPQAEEPHLSPQPEEPCLCAVPEEPHLSPQAEGPHLSPQ 800
801 PEELHLSPQTEEPHLSPVPEEPCLSPQPEESHLSPQSEEPCLSPRPEESH 850
851 LSPELEKPPLSPRPEKPPEEPGQCPAPEELPLFPPPGEPSLSPLLGEPAL 900
901 SEPGEPPLSPLPEELPLSPSGEPSLSPQLMPPDPLPPPLSPIITAAAPPA 950
951 LSPLGELEYPFGAKGDSDPESPLAAPILETPISPPPEANCTDPEPVPPMI 1000
1001 LPPSPGSPVGPASPILMEPLPPQCSPLLQHSLVPQNSPPSQCSPPALPLS 1050
1051 VPSPLSPIGKVVGVSDEAELHEMETEKVSEPECPALEPSATSPLPSPMGD 1100
1101 LSCPAPSPAPALDDFSGLGEDTAPLDGIDAPGSQPEPGQTPGSLASELKG 1150
1151 SPVLLDPEELAPVTPMEVYPECKQTAGQGSPCEEQEEPRAPVAPTPPTLI 1200
1201 KSDIVNEISNLSQGDASASFPGSEPLLGSPDPEGGGSLSMELGVSTDVSP 1250
1251 ARDEGSLRLCTDSLPETDDSLLCDAGTAISGGKAEGEKGRRRSSPARSRI 1300
1301 KQGRSSSFPGRRRPRGGAHGGRGRGRARLKSTASSIETLVVADIDSSPSK 1350
1351 EEEEEDDDTMQNTVVLFSNTDKFVLMQDMCVVCGSFGRGAEGHLLACSQC 1400
1401 SQCYHPYCVNSKITKVMLLKGWRCVECIVCEVCGQASDPSRLLLCDDCDI 1450
1451 SYHTYCLDPPLLTVPKGGWKCKWCVSCMQCGAASPGFHCEWQNSYTHCGP 1500
1501 CASLVTCPICHAPYVEEDLLIQCRHCERWMHAGCESLFTEDDVEQAADEG 1550
1551 FDCVSCQPYVVKPVAPVAPPELVPMKVKEPEPQYFRFEGVWLTETGMALL 1600
1601 RNLTMSPLHKRRQRRGRLGLPGEAGLEGSEPSDALGPDDKKDGDLDTDEL 1650
1651 LKGEGGVEHMECEIKLEGPVSPDVEPGKEETEESKKRKRKPYRPGIGGFM 1700
1701 VRQRKSHTRTKKGPAAQAEVLSGDGQPDEVIPADLPAEGAVEQSLAEGDE 1750
1751 KKKQQRRGRKKSKLEDMFPAYLQEAFFGKELLDLSRKALFAVGVGRPSFG 1800
1801 LGTPKAKGDGGSERKELPTSQKGDDGPDIADEESRGLEGKADTPGPEDGG 1850
1851 VKASPVPSDPEKPGTPGEGMLSSDLDRISTEELPKMESKDLQQLFKDVLG 1900
1901 SEREQHLGCGTPGLEGSRTPLQRPFLQGGLPLGNLPSSSPMDSYPGLCQS 1950
1951 PFLDSRERGGFFSPEPGEPDSPWTGSGGTTPSTPTTPTTEGEGDGLSYNQ 2000
2001 RSLQRWEKDEELGQLSTISPVLYANINFPNLKQDYPDWSSRCKQIMKLWR 2050
2051 KVPAADKAPYLQKAKDNRAAHRINKVQKQAESQINKQTKVGDIARKTDRP 2100
2101 ALHLRIPPQPGALGSPPPAAAPTIFIGSPTTPAGLSTSADGFLKPPAGSV 2150
2151 PGPDSPGELFLKLPPQVPAQVPSQDPFGLAPAYPLEPRFPTAPPTYPPYP 2200
2201 SPTGAPAQPPMLGASSRPGAGQPGEFHTTPPGTPRHQPSTPDPFLKPRCP 2250
2251 SLDNLAVPESPGVGGGKASEPLLSPPPFGESRKALEVKKEELGASSPSYG 2300
2301 PPNLGFVDSPSSGTHLGGLELKTPDVFKAPLTPRASQVEPQSPGLGLRPQ 2350
2351 EPPPAQALAPSPPSHPDIFRPGSYTDPYAQPPLTPRPQPPPPESCCALPP 2400
2401 RSLPSDPFSRVPASPQSQSSSQSPLTPRPLSAEAFCPSPVTPRFQSPDPY 2450
2451 SRPPSRPQSRDPFAPLHKPPRPQPPEVAFKAGSLAHTSLGAGGFPAALPA 2500
2501 GPAGELHAKVPSGQPPNFVRSPGTGAFVGTPSPMRFTFPQAVGEPSLKPP 2550
2551 VPQPGLPPPHGINSHFGPGPTLGKPQSTNYTVATGNFHPSGSPLGPSSGS 2600
2601 TGESYGLSPLRPPSVLPPPAPDGSLPYLSHGASQRSGITSPVEKREDPGT 2650
2651 GMGSSLATAELPGTQDPGMSGLSQTELEKQRQRQRLRELLIRQQIQRNTL 2700
2701 RQEKETAAAAAGAVGPPGSWGAEPSSPAFEQLSRGQTPFAGTQDKSSLVG 2750
2751 LPPSKLSGPILGPGSFPSDDRLSRPPPPATPSSMDVNSRQLVGGSQAFYQ 2800
2801 RAPYPGSLPLQQQQQQLWQQQQATAATSMRFAMSARFPSTPGPELGRQAL 2850
2851 GSPLAGISTRLPGPGEPVPGPAGPAQFIELRHNVQKGLGPGGTPFPGQGP 2900
2901 PQRPRFYPVSEDPHRLAPEGLRGLAVSGLPPQKPSAPPAPELNNSLHPTP 2950
2951 HTKGPTLPTGLELVNRPPSSTELGRPNPLALEAGKLPCEDPELDDDFDAH 3000
3001 KALEDDEELAHLGLGVDVAKGDDELGTLENLETNDPHLDDLLNGDEFDLL 3050
3051 AYTDPELDTGDKKDIFNEHLRLVESANEKAEREALLRGVEPGPLGPEERP 3100
3101 PPAADASEPRLASVLPEVKPKVEEGGRHPSPCQFTIATPKVEPAPAANSL 3150
3151 GLGLKPGQSMMGSRDTRMGTGPFSSSGHTAEKASFGATGGPPAHLLTPSP 3200
3201 LSGPGGSSLLEKFELESGALTLPGGPAASGDELDKMESSLVASELPLLIE 3250
3251 DLLEHEKKELQKKQQLSAQLQPAQQQQQQQQQHSLLSAPGPAQAMSLPHE 3300
3301 GSSPSLAGSQQQLSLGLAGARQPGLPQPLMPTQPPAHALQQRLAPSMAMV 3350
3351 SNQGHMLSGQHGGQAGLVPQQSSQPVLSQKPMGTMPPSMCMKPQQLAMQQ 3400
3401 QLANSFFPDTDLDKFAAEDIIDPIAKAKMVALKGIKKVMAQGSIGVAPGM 3450
3451 NRQQVSLLAQRLSGGPSSDLQNHVAAGSGQERSAGDPSQPRPNPPTFAQG 3500
3501 VINEADQRQYEEWLFHTQQLLQMQLKVLEEQIGVHRKSRKALCAKQRTAK 3550
3551 KAGREFPEADAEKLKLVTEQQSKIQKQLDQVRKQQKEHTNLMAEYRNKQQ 3600
3601 QQQQQQQQQQQQHSAVLALSPSQSPRLLTKLPGQLLPGHGLQPPQGPPGG 3650
3651 QAGGLRLTPGGMALPGQPGGPFLNTALAQQQQQQHSGGAGSLAGPSGGFF 3700
3701 PGNLALRSLGPDSRLLQERQLQLQQQRMQLAQKLQQQQQQQQQQQHLLGQ 3750
3751 VAIQQQQQQGPGVQTNQALGPKPQGLMPPSSHQGLLVQQLSPQPPQGPQG 3800
3801 MLGPAQVAVLQQQHPGALGPQGPHRQVLMTQSRVLSSPQLAQQGQGLMGH 3850
3851 RLVTAQQQQQQQQHQQQGSMAGLSHLQQSLMSHSGQPKLSAQPMGSLQQL 3900
3901 QQQQQLQQQQQLQQQQQQQLQQQQQLQQQQLQQQQQQQQLQQQQQQQLQQ 3950
3951 QQQQLQQQQQQQQQQFQQQQQQQQMGLLNQSRTLLSPQQQQQQQVALGPG 4000
4001 MPAKPLQHFSSPGALGPTLLLTGKEQNTVDPAVSSEATEGPSTHQGGPLA 4050
4051 IGTTPESMATEPGEVKPSLSGDSQLLLVQPQPQPQPSSLQLQPPLRLPGQ 4100
4101 QQQQVSLLHTAGGGSHGQLGSGSSSEASSVPHLLAQPSVSLGDQPGSMTQ 4150
4151 NLLGPQQPMLERPMQNNTGPQPPKPGPVLQSGQGLPGVGIMPTVGQLRAQ 4200
4201 LQGVLAKNPQLRHLSPQQQQQLQALLMQRQLQQSQAVRQTPPYQEPGTQT 4250
4251 SPLQGLLGCQPQLGGFPGPQTGPLQELGAGPRPQGPPRLPAPPGALSTGP 4300
4301 VLGPVHPTPPPSSPQEPKRPSQLPSPSSQLPTEAQLPPTHPGTPKPQGPT 4350
4351 LEPPPGRVSPAAAQLADTLFSKGLGPWDPPDNLAETQKPEQSSLVPGHLD 4400
4401 QVNGQVVPEASQLSIKQEPREEPCALGAQSVKREANGEPIGAPGTSNHLL 4450
4451 LAGPRSEAGHLLLQKLLRAKNVQLSTGRGSEGLRAEINGHIDSKLAGLEQ 4500
4501 KLQGTPSNKEDAAARKPLTPKPKRVQKASDRLVSSRKKLRKEDGVRASEA 4550
4551 LLKQLKQELSLLPLTEPAITANFSLFAPFGSGCPVNGQSQLRGAFGSGAL 4600
4601 PTGPDYYSQLLTKNNLSNPPTPPSSLPPTPPPSVQQKMVNGVTPSEELGE 4650
4651 HPKDAASARDSERALRDTSEVKSLDLLAALPTPPHNQTEDVRMESDEDSD 4700
4701 SPDSIVPASSPESILGEEAPRFPHLGSGRWEQEDRALSPVIPLIPRASIP 4750
4751 VFPDTKPYGALGLEVPGKLPVTTWEKGKGSEVSVMLTVSAAAAKNLNGVM 4800
4801 VAVAELLSMKIPNSYEVLFPESPARAGTEPKKGEAEGPGGKEKGLEGKSP 4850
4851 DTGPDWLKQFDAVLPGYTLKSQLDILSLLKQESPAPEPPTQHSYTYNVSN 4900
4901 LDVRQLSAPPPEEPSPPPSPLAPSPASPPTEPLVELPTEPLAEPPVPSPL 4950
4951 PLASSPESARPKPRARPPEEGEDSRPPRLKKWKGVRWKRLRLLLTIQKGS 5000
5001 GRQEDEREVAEFMEQLGTALRPDKVPRDMRRCCFCHEEGDGATDGPARLL 5050
5051 NLDLDLWVHLNCALWSTEVYETQGGALMNVEVALHRGLLTKCSLCQRTGA 5100
5101 TSSCNRMRCPNVYHFACAIRAKCMFFKDKTMLCPMHKIKGPCEQELSSFA 5150
5151 VFRRVYIERDEVKQIASIIQRGERLHMFRVGGLVFHAIGQLLPHQMADFH 5200
5201 SATALYPVGYEATRIYWSLRTNNRRCCYRCSIGENNGRPEFVIKVIEQGL 5250
5251 EDLVFTDASPQAVWNRIIEPVAAMRKEADMLRLFPEYLKGEELFGLTVHA 5300
5301 VLRIAESLPGVESCQNYLFRYGRHPLMELPLMINPTGCARSEPKILTHYK 5350
5351 RPHTLNSTSMSKAYQSTFTGETNTPYSKQFVHSKSSQYRRLRTEWKNNVY 5400
5401 LARSRIQGLGLYAAKDLEKHTMVIEYIGTIIRNEVANRREKIYEEQNRGI 5450
5451 YMFRINNEHVIDATLTGGPARYINHSCAPNCVAEVVTFDKEDKIIIISSR 5500
5501 RIPKGEELTYDYQFDFEDDQHKIPCHCGAWNCRKWMN 5537
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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