 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O88737 from www.uniprot.org...
The NucPred score for your sequence is 0.97 (see score help below)
1 MGNEASLEGGAGEGPLPPGGSGLGPGPGAGKPPSALAGGGQLPVAGAARA 50
51 AGPPTPGLGPVPGPGPGPGPGSVPRRLDPKEPLGSQRTTSPTPKQASATA 100
101 PGRESPRETRAQGPSGQEAESPRRTLQVDSRTQRSGRSPSVSPDRGSTPT 150
151 SPYSVPQIAPLPSSTLCPICKTSDLTSTPSQPNFNTCTQCHNKVCNQCGF 200
201 NPNPHLTQVKEWLCLNCQMQRALGMDMTTAPRSKSQQQLHSPALSPAHSP 250
251 AKQPLGKPEQERSPRGPGATQSGPRQAEAARATSVPGPTQATAPPEVGRV 300
301 SPQPPLSTKPSTAEPRPPAGEAQGKSATTVPSGLGAGEQTQEGLTGKLFG 350
351 LGASLLTQASTLMSVQPEADTQGQPSPSKGQPKIVFSDASKEAGPRPPGS 400
401 GPGPGPTPGAKTEPGARMGPGSGPGALAKTGGTASPKHGRAEHQAASKAA 450
451 AKPKTMPKERASACPLCQAELNMGSRGPANYNTCTACKLQVCNLCGFNPT 500
501 PHLVEKTEWLCLNCQTKRLLEGSLGEPAPLPLPTPQQPPAGVPHRAAGAA 550
551 PLKQKGPQGLGQPSGSLPAKASPQATKASPQATKASPQATKASPQTTKAS 600
601 PQAKPLRATEPSKTSSSAQEKKTVTSAKAEPVPKPPPETTVPPGTPKAKS 650
651 GVKRTDPATPVVKPVPEAPKGGEAEEPVPKPYSQDLSRSPQSLSDTGYSS 700
701 DGVSSSQSEITGVVQQEVEQLDSAGVTGPRPPSPSELHKVGSSLRPSLEA 750
751 QAVAPSAEWSKPPRSSSSAVEDQKRRPHSLSITPEAFDSDEELGDILEED 800
801 DSLAWGRQREQQDTAESSDDFGSQLRHDYVEDSSEGGLSPLPPQPPARAD 850
851 MTDEEFMRRQILEMSAEEDNLEEDDTAVSGRGLAKHSAQKASARPRPESS 900
901 QEPKRRLPHNATTGYEELLSEAGPAEPTDSSGALQGGLRRFKTIELNSTG 950
951 SYGHELDLGQGPDPNLDREPELEMESLTGSPEDRSRGEHSSTLPASTPSY 1000
1001 TSGTSPTSLSSLEEDSDSSPSRRQRLEEAKQQRKARHRSHGPLLPTIEDS 1050
1051 SEEEELREEEELLREQEKMREVEQQRIRSTARKTRRDKEELRAQRRRERS 1100
1101 KTPPSNLSPIEDASPTEELRQAAEMEELHRSSCSEYSPSPSLDSEAETLD 1150
1151 GGPTRLYKSGSEYNLPAFMSLYSPTETPSGSSTTPSSGRPLKSAEEAYED 1200
1201 MMRKAEMLQRQQGQVAGARGPHGGPSQPTGPRSQGSFEYQDTQDHDYGGR 1250
1251 ASQPVAESTPAGLGAAVYEEILQTSQSIARMRQASSRDLGFTEDKKKEKQ 1300
1301 FLNAESAYMDPMKQNGGPLTPGTSPTQLAAPVSFSTSTSSDSSGGRVIPD 1350
1351 VRVTQHFAKEPQDPLKLHSSPVSSTLTSKEVGMTFSQGPGSPATTASPTR 1400
1401 GYMTPTSPAGSERSPSTSSTIHSYGQPPTTANYGSQTEELPHAPSGPPGS 1450
1451 GRAPREKPLSGGDSEVGAPQPSRGYSYFTGSSPPLSPSTPSESPTFSPGK 1500
1501 LGPRATAEFSTQTPSLTLSSDIPRSPGPPSPMVAQGTQTPHRPSTPRLVW 1550
1551 QQSSQEAPIMVITLASDASSQTRMVHASASTSPLCSPTDSQPTSHSYSQT 1600
1601 TPPSASQMPSEPAGPPGFPRAPSAGTDGPLALYGWGALPAENISLCRISS 1650
1651 VPGTSRVEPGPRPPGTAVVDLRTAVKPTPIILTDQGMDLTSLAVEARKYG 1700
1701 LALDPVSGRQSTAVQPLVINLNAQEQTHTFLATATTVSITMASSVLMAQQ 1750
1751 KQPVVYGDPFQSRLDFGQGSGSPVCLAQVKQVEQAVQTAPYRGGPRGRPR 1800
1801 EAKFARYNLPNQVTPLARRDILITQMGTAQGVGLKPGPVPEPGAEPHRAT 1850
1851 PAELRSHAPPGTRKPHTVVVQMGEGTAGTVTTLLPEEPAGALDLTGMRPE 1900
1901 SQLACCDMVYKFPFGSSCTGTFHPAPSAPDKSVTDTALPGQSSGPFYSPR 1950
1951 DPEPPEPLTFRTQGVVGPGPHEEQRPYPQGLPGRLYSSMSDTNLAEAGLN 2000
2001 YHAQRLGQLFQGPGRDSAVDLSSLKHSYSLGFADGRYLGQGLQYGSFTDL 2050
2051 RHPTDLLSHPLPLRRYSSVSNIYSDHRYGPRGDAVGFQEASLAQYSATTA 2100
2101 REISRMCAALNSMDQYGGRHGSGSGGPDLVQYQPQHGPGLSAPQGLAPLR 2150
2151 SGLLGNPTYPEGQPSPGNLAQYGPAASQATAVRQLLPSTATVRAADGMIY 2200
2201 STINTPIAATLPITTQPASVLRPMVRGGMYRPYVSGGVTAVPLTSLTRVP 2250
2251 MIAPRVPLGPAGLYRYPAPRFPIASSVPPAEGPVYLGKPAAAKASGAGGP 2300
2301 PRPELPAGVAREEPFSTTAPAVIKEAPVAPAPGPAPAPPPGQKPAGEAVA 2350
2351 GSGSGVLSRPASEKEEASQEDRQRKQQEQLLQLERERVELEKLRQLRLQE 2400
2401 ELERERVELQRHREEEQLLVQRELQELQTIKQHVLQQQQEERQAQFALQR 2450
2451 EQLAQQRLQLEQIQQLQQQLQLQLEEQKQRQKAPFPATCEAPSRGPPPAA 2500
2501 TELAQNGQYWPPLTHAAFIAVAGTEGPGQPREPVLHRGLPSSASDMSLQT 2550
2551 EEQWEAGRSGIKKRHSMPRLRDACEPESGPDPSTVRRIADSSVQTDDEEG 2600
2601 EGRYLVTRRRRTRRSADCSVQTDDEDNADWEQPVRRRRSRLSRHSDSGSD 2650
2651 SKHDATASSSTTAAATARAMSSVGIQTISDCSVQTEPEQLPRVSPAIHIT 2700
2701 AATDPKVEIVRYISAPEKTGRGESLACQTEPDGQAQGVAGPQLIGPTAIS 2750
2751 PYLPGIQIVTPGALGRFEKKKPDPLEIGYQAHLPPESLSQLVSRQPPKSP 2800
2801 QVLYSPVSPLSPHRLLDTSFASSERLNKAHVSPQKQFIADSTLRQQTLPR 2850
2851 PMKTLQRSLSDPKPLSPTAEESAKERFSLYQHQGGLGSQVSALPPNGLVR 2900
2901 KVKRTLPSPPPEEAHLPLAGQVPSQLYAASLLQRGLAGPTTVPATKASLL 2950
2951 RELDRDLRLVEHESTKLRKKQAELDEEEKEIDAKLKYLELGITQRKESLA 3000
3001 KDRGGRDYPPLRGLGEHRDYLSDSELNQLRLQGCTTPAGQYVDYPASAAV 3050
3051 PATPSGPTAFQQPRFPPAAPQYTAGSSGPTQNGFPAHQAPTYTGPSTYPA 3100
3101 PTYPPGTGYPAEPGLPSQPAFHPTGHYAAPTPMPTTQSAPFPVQADSRAA 3150
3151 HQKPRQTSLADLEQKVPTNYEVIGSPAVTMSSAPPETGYSGPAVSGSYEQ 3200
3201 GKAPEHPRGSDRSSVSQSPAPTYPSDSHYTSLEQNVPRNYVMIDDISELT 3250
3251 KDSTPTASESQRLEPLGPGGVSGRPGKDPGEPAVLEGPTLPCCYGRGEEE 3300
3301 SEEDSYDPRGKSGHHRSMESNGRPSTHYYGDSDYRHGARADKYGPGPMGP 3350
3351 KHPSKSLAPAAISSKRSKHRKQGMEQKISKFSPIEEAKDVESDLASYPPP 3400
3401 TVSSSLTSRGRKFQDEITYGLKKNVYEQQRYYGVSSRDAAEEDERMYGSS 3450
3451 SRSRMASAYSGEKLSSHDYSSRGKGYERERDTAERLQKAGSKPSSLSMAH 3500
3501 GRARPPMRSQASEEESPVSPLGRPRPAGGALPPGDTCPQFCSSHSMPDVQ 3550
3551 EHVKDGPRAHAYKREEGYMLDDSHCVVSDSEAYHLGQEETDWFDKPRDAR 3600
3601 SDRFRHHGGHTVSSSQKRGPARHSYHDYDEPPEEGLWPHDEGGPGRHTSA 3650
3651 KEHRHHSDHGRHSGRHAGEEPGRRAAKPHARDMGRHEARPHPQASPAPAM 3700
3701 QKKGQPGYPSSADYSQSSRAPSAYHHASESKKGSRQAHTGPSALQPKADT 3750
3751 QAQPQMQGRQAAPGPQQSQPPSSRQTPSGTASRQPQTQQQQQQQQQQQGL 3800
3801 GQQAPQQAPSQARLQPQSQPTTRGTAPAASQPAGKPQPGPTTAPGPQPAG 3850
3851 PPRAEQASSSKPPAAKAPQQGRAPQAQTTPGPGPAGAKPGARPGGTPGAP 3900
3901 ASQPGAEGESVFSKILPGGAAEQAGKLTEAVSAFGKKFSSFW 3942
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.) |
Go back to the NucPred Home Page.