 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9W596 from www.uniprot.org...
The NucPred score for your sequence is 0.91 (see score help below)
1 MGDQPKATTTATGGAAGPVPEGDAVMATTNQDALAKGAGDGPAQDAAQEP 50
51 GQAEHGEPGDGGDGGDDGATDAGASSLPPSEIGGRAPLDTACSDADGGAP 100
101 SSLAGGIVGPPSPLTGCYLLIVLGEPHSEEHKDNILQHLLKGFLSWDVSD 150
151 CHVDLEEELNTITQHAPEGEEARHGERLIQYASENLVTEVLIHPQYNTLI 200
201 QCMRNLLSSFTRHRHIIHAGYTFSGNGSWILQDGTFSVADFSEAFQEHDV 250
251 QRVIRAYADTITMNIHCADAGLWHTLPEKAFARQCRIRINPVDVLDTSSE 300
301 CINGFIDYLAPMVMPTSLRELLETSDVVGNIRFTHPTLYVFPGGQGDAAL 350
351 FGINGFNMLVDGGFNRKACFWDFARHLDRLDAVLMTRLNNSNVQGLGAVV 400
401 SRKRDAHVYPQIGHFFGNVPDRKGLPSPDGDKDRDPLLIDLFERGHGIVS 450
451 DLKALDLKPQCCYRNQEPVNLYHKVGHGTLDMYVISPARDSKEVKEFLQK 500
501 WHAGDQRLFAARDSRDFNFPLQNLVSICALLVWQPANPDDTITRILFPGS 550
551 TPDFKIQEGLEKLKHLEFMKHSTCTAKSIAPAIQTVTSTRKSLKSAIEAT 600
601 PAPPSASYKTTKFSPVASAALAVQHPQQQDNKAKEAAAAAAAAAAAAASA 650
651 ATIARAKADSMDTDAEPEHEADPEPADTGDEAAPTEQEPEAETEPEPEHE 700
701 PEAEQDKDVGEEKKVEVLIMKPQQATPAVIAASGKDGVDAASADATPTGK 750
751 LSKASAKGKADKPRAEVKPVVRSRIDTKPPKSMDRKLAKRDEKKSSPTTT 800
801 PAARAPVAQNAKPKVLSRPATKSSPSSTPAKSAKEANNRKVLESKQQAAR 850
851 VQATSTVSRRVTSTASERRVQQQAEAKTAATGATQATQRKPISRRPRGVS 900
901 PSKRAPAPGSPVKQAKPKAADLKKTRLDKGGTTDSSLVSTPSADEATAAK 950
951 KLQDLTASQELDAEKQRELDDLKEEQEVVREIEAVFSRDEMKRQQHQQIK 1000
1001 AELREMPAEGTGDGENEPDEEEEYLIIEKEEVEQYTEDSIVEQESSMTKE 1050
1051 EEIQKHQRDSQESEKKRKKSAEEEIEAAIAKVEAAERKARLEGASARQDE 1100
1101 SELDVEPEQSKIKAEVQDIIATAKDIAKSRTEEQLAKPAEEELSSPTPEE 1150
1151 KLSKKTSDTKDDQIGAPVDVLPVNLQESLPEEKFSATIESGATTAPTLPE 1200
1201 DERIPLDQIKEDLVIEEKYVKEETKEAEAIVVATVQTLPEAAPLAIDTIL 1250
1251 ASATKDAPKDANAEALGELPDSGERVLPMKMTFEAQQNLLRDVIKTPDEV 1300
1301 ADLPVHEEADLGLYEKDSQDAGAKSISHKEESAKEEKETDDEKENKVGEI 1350
1351 ELGDEPNKVDISHVLLKESVQEVAEKVVVIETTVEKKQEEIVEATTVITQ 1400
1401 ENQEDLMEQVKDKEEHEQKIESGIITEKEAKKSASTPEEKETSDITSDDE 1450
1451 LPAQLADPTTVPPKSAKDREDTGSIESPPTIEEAIEVEVQAKQEAQKPVP 1500
1501 APEEAIKTEKSPLASKETSRPESATGSVKEDTEQTKSKKSPVPSRPESEA 1550
1551 KDKKSPFASGEASRPESVAESVKDEAGKAESRRESIAKTHKDESSLDKAK 1600
1601 EQESRRESLAESIKPESGIDEKSALASKEASRPESVTDKSKEPSRRESIA 1650
1651 ESLKAESTKDEKSAPPSKEASRPGSVVESVKDETEKSKEPSRRESIAESA 1700
1701 KPPIEFREVSRPESVIDGIKDESAKPESRRDSPLASKEASRPESVLESVK 1750
1751 DEPIKSTEKSRRESVAESFKADSTKDEKSPLTSKDISRPESAVENVMDAV 1800
1801 GSAERSQPESVTASRDVSRPESVAESEKDDTDKPESVVESVIPASDVVEI 1850
1851 EKGAADKEKGVFVSLEIGKPDSPSEVISRPGPVVESVKPESRRESSTEIV 1900
1901 LPCHAEDSKEPSRPESKVECLKDESEVLKGSTRRESVAESDKSSQPFKET 1950
1951 SRPESAVGSMKDESMSKEPSRRESVKDGAAQSRETSRPASVAESAKDGAD 2000
2001 DLKELSRPESTTQSKEAGSIKDEKSPLASEEASRPASVAESVKDEAEKSK 2050
2051 EESRRESVAEKSPLPSKEASRPASVAESIKDEAEKSKEESRRESVAEKSP 2100
2101 LPSKEASRPASVAESIKDEAEKSKEESRRESVAEKSPLPSKEASRPASVA 2150
2151 ESIKDEAEKSKEESRRESVAEKSPLPSKEASRPASVAESIKDEAEKSKEE 2200
2201 SRRESVAEKSPLPSKEASRPASVAESIKDEAEKSKEESRRESVAEKSPLP 2250
2251 SKEASRPASVAESIKDEAEKSKEESRRESVAEKSPLPSKEASRPASVAES 2300
2301 IKDEAEKSKEETRRESVAEKSPLPSKEASRPASVAESIKDEAEKSKEESR 2350
2351 RESAAEKSPLPSKEASRPASVAESVKDEADKSKEESRRESMAESGKAQSI 2400
2401 KGDQSPLKEVSRPESVAESVKDDPVKSKEPSRRESVAGSVTADSARDDQS 2450
2451 PLESKGASRPESVVDSVKDEAEKQESRRESKTESVIPPKAKDDKSPKEVL 2500
2501 QPVSMTETIREDADQPMKPSQAESRRESIAESIKASSPRDEKSPLASKEA 2550
2551 SRPGSVAESIKYDLDKPQIIKDDKSTEHSRRESLEDKSAVTSEKSVSRPL 2600
2601 SVASDHEAAVAIEDDAKSSISPKDKSRPGFVAETVSSPIEEATMEFSKIE 2650
2651 VVEKSSLALSLQGGSGGKLQTDSSPVDVAEGDFSHAVASVSTVTPTLTKP 2700
2701 AELAQIGAAKTVSSPLDEALRTPSAPEHISRADSPAECASEEIASQDKSP 2750
2751 QVLKESSRPAWVAESKDDAAQLKSSVEDLRSPVASTEISRPASAGETASS 2800
2801 PIEEAPKDFAEFEQAEKAVLPLTIELKGNLPTLSSPVDVAHGDFPQTSTP 2850
2851 TSSPTVASVQPAELSKVDIEKTASSPIDEAPKSLIGCPAEERPESPAESA 2900
2901 KDAAESVEKSKDASRPPSVVESTKADSTKGDISPSPESVLEGPKDDVEKS 2950
2951 KESSRPPSVSASITGDSTKDVSRPASVVESVKDEHDKAESRRESIAKVES 3000
3001 VIDEAGKSDSKSSSQDSQKDEKSTLASKEASRRESVVESSKDDAEKSESR 3050
3051 PESVIASGEPVPRESKSPLDSKDTSRPGSMVESVTAEDEKSEQQSRRESV 3100
3101 AESVKADTKKDGKSQEASRPSSVDELLKDDDEKQESRRQSITGSHKAMST 3150
3151 MGDESPMDKADKSKEPSRPESVAESIKHENTKDEESPLGSRRDSVAESIK 3200
3201 SDITKGEKSPLPSKEVSRPESVVGSIKDEKAESRRESVAESVKPESSKDA 3250
3251 TSAPPSKEHSRPESVLGSLKDEGDKTTSRRVSVADSIKDEKSLLVSQEAS 3300
3301 RPESEAESLKDAAAPSQETSRPESVTESVKDGKSPVASKEASRPASVAEN 3350
3351 AKDSADESKEQRPESLPQSKAGSIKDEKSPLASKDEAEKSKEESRRESVA 3400
3401 EQFPLVSKEVSRPASVAESVKDEAEKSKEESPLMSKEASRPASVAGSVKD 3450
3451 EAEKSKEESRRESVAEKSPLPSKEASRPASVAESVKDEADKSKEESRRES 3500
3501 GAEKSPLASKEASRPASVAESIKDEAEKSKEESRRESVAEKSPLPSKEAS 3550
3551 RPTSVAESVKDEAEKSKEESRRDSVAEKSPLASKEASRPASVAESVQDEA 3600
3601 EKSKEESRRESVAEKSPLASKEASRPASVAESIKDEAEKSKEESRRESVA 3650
3651 EKSPLASKEASRPTSVAESVKDEAEKSKEESSRDSVAEKSPLASKEASRP 3700
3701 ASVAESVQDEAEKSKEESRRESVAEKSPLASKEASRPASVAESVKDDAEK 3750
3751 SKEESRRESVAEKSPLASKEASRPASVAESVKDEAEKSKEESRRESVAEK 3800
3801 SPLPSKEASRPTSVAESVKDEAEKSKEESRRESVAEKSSLASKKASRPAS 3850
3851 VAESVKDEAEKSKEESRRESVAEKSPLASKEASRPASVAESVKDEAEKSK 3900
3901 EESRRESVAEKSPLPSKEASRPTSVAESVKDEADKSKEESRRESGAEKSP 3950
3951 LASMEASRPTSVAESVKDETEKSKEESRRESVTEKSPLPSKEASRPTSVA 4000
4001 ESVKDEAEKSKEESRRESVAEKSPLASKESSRPASVAESIKDEAEGTKQE 4050
4051 SRRESMPESGKAESIKGDQSSLASKETSRPDSVVESVKDETEKPEGSAID 4100
4101 KSQVASRPESVAVSAKDEKSPLHSRPESVADKSPDASKEASRSLSVAETA 4150
4151 SSPIEEGPRSIADLSLPLNLTGEAKGKLPTLSSPIDVAEGDFLEVKAESS 4200
4201 PRPAVLSKPAEFSQPDTGHTASTPVDEASPVLEEIEVVEQHTTSGVGATG 4250
4251 ATAETDLLDLTETKSETVTKQSETTLFETLTSKVESKVEVLESSVKQVEE 4300
4301 KVQTSVKQAETTVTDSLEQLTKKSSEQLTEIKSVLDTNFEEVAKIVADVA 4350
4351 KVLKSDKDITDIIPDFDERQLEEKLKSTADTEEESDKSTRDEKSLEISVK 4400
4401 VEIESEKSSPDQKSGPISIEEKDKIEQSEKAQLRQGILTSSRPESVASQP 4450
4451 ESVPSPSQSAASHEHKEVELSESHKAEKSSRPESVASQVSEKDMKTSRPA 4500
4501 SSTSQFSTKEGDEETTESLLHSLTTTETVETKQMEEKSSFESVSTSVTKS 4550
4551 TVLSSQSTVQLREESTSESLSSSLKVEDSSRRESLSSLLAEKGGIATNTS 4600
4601 LKEDTSASASQLEELLVQSEECSSESIVSEIQTSIAQKSNKEIKDARETK 4650
4651 VTSQFTTTTSSATKDDSLKETVAEFLATEKIVSAKEAFSTEATKSADDCL 4700
4701 KKTTASAVSSTSASQRALFVGTDESRRESLLSQASESRLTHSDPEDEEPA 4750
4751 DDVDERSSVKESRSKSIATIMMTSIYKPSEDMEPISKLVEEEHEHVEELA 4800
4801 QEVTSTSKTTTLLQSSEQSSTTTSSTSKTGASRVESITLTQMDQQTSQSQ 4850
4851 GDPADRKTPPTAPVSPGVKAMSSTGSAGSVIGAGAGAVAAGGKCESSAAS 4900
4901 IVSSSGPMSPKDISGKSSPGALTSESQSIPTPLGRESHTDTPESSPKPTS 4950
4951 PFPRVSKDELKSLEMQHHSQEQMLAGAAAAAGAECEGDIPELHELRGLEC 5000
5001 TTALSGSTDKIITTTITTVTKVISADGKEIVTEQKTVTTTDSSEPDSEKV 5050
5051 VVTTTRTTSESERDQLLPKEVALLRGLYRASTPGSEDDEDLLLGSPRSAT 5100
5101 SYELQHSSSGVSKRSDLDADGDESQDDIPPQYGSEEHSTARSILLPRTAD 5150
5151 PMATSFYGALPDSFDVVMKPSTEPIPIQGAPSGDSQSSESVESSSQTWAG 5200
5201 HKFLDQADKDFQRALEEHVQARGAEVMSSVTAKYSYSPSKAEEMEQIVSG 5250
5251 TAERQRFPLSDVQRARVAESGFATVGSVASQQQQQEKGGEVEQAVPTTTA 5300
5301 VTASTTATASSTGALPKDRLEEWGKPLGLPSPAPLPVEGGADIRTTPKKE 5350
5351 RRLVATKTRLNNEKNLRRRSESPNKAGKKPAPVYVDLTYVPHNGNSYYAH 5400
5401 VDFFKRVRARYYVFSGTEPSRQVYDALLEAKQTWEDKELEVTIIPTYDTD 5450
5451 VLGYWVAENEELLAKHRIDLSPSASRCTINLQDHETSCSAYRLEF 5495
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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