 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9DEI1 from www.uniprot.org...
The NucPred score for your sequence is 0.96 (see score help below)
1 MLLAGAGGSSGDGQDGVASGPAESAAGILGRLHQLHGLLSLESGVGAEGA 50
51 HSLLHNLAEECLVSALGSSALDLNTSLIFSKEFGLLAFVRKSLSSDEFKD 100
101 CREEALKFLYTFLEKIGSNVQPYAMDIKTLCVIVYTKDRAAKCKIPSLEL 150
151 LIKLLQLLKNSIIIEEFKIGEIFNKFYGELATKSKLSDTVLEKVYELLGI 200
201 LGEVQPCEMTYNSEKLFKAFLGELKAQMNSSTRNPKFPVIAGCLKGLSAL 250
251 MINFTKTMEEDPRTSKEIFDYTVKAISPQVEMKRYAVPSAGLNLLALHAS 300
301 QFSSYLMDDYQSLFEVISKWCGHTNGEMKKLAFAALDSFLKQIAHLVASD 350
351 AETHKNKLHFFMEQFYEIIRKMDSSNKELSIAIRGYGLFAAPCKAVNAKN 400
401 VDLMYIELIQRCKQMYLTEADTEEDNVYQLPNFLQSVASVILHMDSIPEV 450
451 YTPILERLLVVQIDSFPQYSLKMQSSCCKAVLKVFLSLAGKGPVLWSLIS 500
501 TVVHQGLIRVCSKPVVLAQDGKEGSEAETAAATGEVRAGKWKVPTYKDYL 550
551 DLFRNLLRCDQLKDSIFSDEIFSTVNSPLQSLNRLLYDELMKSILKIIEK 600
601 LDLSLQKQDTGQEDDGGINNLLINATSDPAGNLYATKPKDFTAFVNLVEF 650
651 CSEILPKEHIEYFESWVYVFGYELVLQSTRLPLISGFYKLLSVVMKNAKK 700
701 SRYFEGFTSKIYKKAPEDPERLSCFALFAKFGKEVSSKIRQFKDELLASC 750
751 LTFVLHLPHDIIMMDIKAYIPALQTAFKLGLSCPPLADVGLNALQYWSTN 800
801 IPSDILKPYYKDIIPLLDGYLTNLSSTNESLSTLDMVRISRSLHKGFNKQ 850
851 LIQQLKRMKTLSVKEESSLTAVRNRVVRILGSLGGQINRSLVTAASTEEM 900
901 IKRHVSWDTEKRLRFDVPFKDLKPVIYLDMFLPHITELALSTSDRQTKVA 950
951 ACELLHSIVAFMLGKATQMPDDKKTGSSPMYKIYKRTFPVLLRLACDVDK 1000
1001 VTEQLYKPLVMSLIHWFTNNKKFESQDTVALLEAILTGIVDPVDSTLRDF 1050
1051 CGQCIQEFLRWSIKQTTPDQQAKSPVNTTSLFKRLYSLALHPNAFKRLGA 1100
1101 ALAFNNIYRDFREETALVENFVFEVLVIYMESLALSHADEKSLGTTQQCS 1150
1151 DAVDHLKRIIIRKAASLNKATKRRIPRGFPQGNTVCLFDIVLWLLEQCGR 1200
1201 PQTECRHKAMQLFFEFVPLLPGNKPLTAWLDDQVEKEGIIFLINRFEGAG 1250
1251 HSDGMHTGIFNIPALHDLHEPFSMHAVLQWLDMLLAALDCYNTFIGMRFL 1300
1301 KANTVLGKNAEKSSFLKAAFFFITSLSMENIKAAEQCMGSKSSVFSPHEI 1350
1351 EAYNYSKCTIIVRIMEFITMFIDICQQDSLKILENSVFNEPMWELIAITV 1400
1401 CDPSSIGFNTADVEVINNLPNICIKLMKALGNTSYRSSLEVSLKKRVTLQ 1450
1451 SIEELCSVDLYDPGARFNRVKLGSVLSACKQLYKAEFFNSIVPEQVGGQR 1500
1501 FGSKLLSVVYKGIAPTNERKSLPSLDISSKRLAEGLLELAFMFGGQCEEL 1550
1551 VSLLLNTVILSVPLPGTSQRNIINFSHGGYFYTLFAETINTELLNNLDTI 1600
1601 VVELMKSSLEDPKMVSCVLNGMLDQSFRQRTIRKQQGVKLVNAVLENWRR 1650
1651 LDSWWYKDSPSESKMAVLTLLAKVLQIDSSVCFDINHSAFAEVFKTYTSI 1700
1701 LTDQKLGLNLKSQAIIILPFFTKLTGEKLTELKNTLDQFVASNFPMKSDE 1750
1751 FPKGTLKFNNYVDCIKKFLDALELSQSPMLLQLMTEILCRDERHFMEELF 1800
1801 QSSFKKVIKRSSCDTQVILLNTLHNMFKSESLMLNGTLQSLIDRCLLTLL 1850
1851 WNCSLDAMISFFTNIISLAMDTLKSRFTKVPEAAFDSQITKKWGYYKMLE 1900
1901 VQYSRLSKDEIYSTVNNAYHVSSKPEGNELTKALIKLCYDTFTENMCGET 1950
1951 QLLEKRRQYHCAAYNCAISLISCVFSELKFYQGFLFTEKKEKNLLIFENL 2000
2001 IDLQRNYTFPIEVEVPMERKKKYFAIRKEARDASSTESDEPSYLSSQSYM 2050
2051 ADSSLIEEMSQFDFSTGVQSFSYSSQSKMLSQSASRKKEQITEGKTFDDV 2100
2101 MEFEMDELNQHECMAAMTGLIKHMNRSEITPKVDEDASPQELPSWMKFLH 2150
2151 VKLGNTSTPLNIRLFIAKLIVNTEEVFRPYARFWIGPILQLIVSGNNGGT 2200
2201 GIHYMVVETLVTILSWSSIATPNGQAKEEILANRLLEFLMKNVFHEKRAV 2250
2251 FRHNLEIIKTVLECWKECLSIPYRLIYEGFSGTDPNTKDNSVGIQLLGLA 2300
2301 LANNFSPLDPKCGIDPERYFQSLANNLGLTRFKEVYIAAAEVIGLVLRYI 2350
2351 VQNEKRTEAPVFDYVVKELKRHQTNNKEDKFIMCLNKVVKNFPPFADRFM 2400
2401 TIVLFLLPKLHGVLKTQCLEIIMHRAEDIPDLFIELKNKDFCQIMNNRDD 2450
2451 ERQRVCLDIIYKILSKLTPAELHEFLIPVTAFSSHSFPVCRERMYDIFMW 2500
2501 IYDNYRDHESQNDSKSVEVFNMAKEGLLQGLVDENTELQLIVRNFWSDET 2550
2551 RLPSNTTERMLAILSSLYSPKIEKHYLSLATNLLLEMTSKSPDYIRKMFE 2600
2601 HPLSECKFQDYTVDSSWRFRSSVLTPMFVETQLSQSMQRSRAQGTIEADE 2650
2651 PIGGQLRATQQHYQFTPTQNIGGRSSFNWLTGSSMDTLADYSVESPESLP 2700
2701 SALLFVNKRNENVRRVPLKPLGPNFGMRRLGLPGDVTDSKTKSMEDRSDI 2750
2751 LRLRRRFLKDREKLSLIYARKGTAEQKREKAIKIEQKMKQDAQITLYRNY 2800
2801 RQGELPDIQISYSNLIAPLQALAQRDPTMAKLLFSSLFSGILTDTASDIS 2850
2851 VTDKLLKQFNSFLSNSLSYFPPFIACVQDMCYQHDELLHLNPANISTSCL 2900
2901 ASLQQPLGILLLEKGLLHMKVPDEPPAKKMRKEKEKAEIPPDIVRWIELA 2950
2951 KLYRSIGDYDVLRGIFSGKIGAKSITQCALNAEAKSDYAKAAKLYDEALT 3000
3001 ETFSDGDPTDAEKDFWELASLECYNHLTEWKPLEYCSTVNIDTGKPPDLN 3050
3051 KMWSDPFYQETYLPYMIRSKLKMLLGGNNDQTLLTFVDEAMKVEQRKVLM 3100
3101 ETFYSQELSLLYILQDDFDRAKYYINNGIQVFMQNYSSIDCLLYQSRLTK 3150
3151 LQSVQALTETQDFISFIRKPGNVSSSSLRKLFQGWMKRYPDSKMDPMNIW 3200
3201 DDIISNRCFFLDKIQDVAVGHPQLVDESMEVDDLADGNEAMEVDRQEDIA 3250
3251 VMINKCRFTMKMKMVDSARKQNNFSVAMKLLKDLHRESKTNEDWSVKWIH 3300
3301 SYSRYSHSRSRDLTCSEQILTALKTIPLLEESKTEYLTKNTKACRYQNML 3350
3351 LGDTYRIMADAVCKEPDCLYKIEDGKAGKVKDLSESPENVVGGLYRKSLH 3400
3401 YFTNAVRKATEEEQSHSTDQIDVRGIIKAYMTLVDFCDSHLRKVEEESAV 3450
3451 MDRADYQNFPEIMVEKMIKALKLNSSEARLKFPRMLQIIEQYPSETLDLM 3500
3501 ARENCTVPCWQFIGWISQMMAMLDKKESIAVQHIIEEIAENYPQALVYPF 3550
3551 MVSGESYNFEDTVVGHKNREYVNRIKSKLDKDNVAQDFIRALEQLSNPPM 3600
3601 IFQDWWEDVSNELSKPNVNKNKIKELYKEMYTNLGNPKDHFMGAFRRRFC 3650
3651 EKYTKDFDKAFGPEGSKLLNIKCDGFNKTVGPLITKMKEQQKEPGNLKEY 3700
3701 SPWMSEFKPEFLRNELEIPGQYSGRSKPMPEYHVKISGFDERVSVMASIR 3750
3751 KPKRIIVRGNDEREYPFLVKGGEDLRQDQRIEQLFEIMNIILSQDAACSQ 3800
3801 RHMQLKTYQVIPMTTRIGLIEWLENTCTLKEFILNTMTEDEAKIYNSKTT 3850
3851 NGPLYHYNAWLDKKEKVGDARQHVTSYTRCDRTNTVASFREREALVPKDL 3900
3901 LRRAFVKMSTTPEAFLSLRSHFARSHALLCVSHWIVGIGDRHLSNFMINM 3950
3951 ETGGMIGIDFGHAFGTATQFLPVPELMPFRLTRQIVNLMLPMKDSGLFDS 4000
4001 VMVHSLRAYRSDPGLLVTTMDVFIKEPSLDWKNLELKQMKKKGEWKKAVD 4050
4051 VTSHNWHPQQKIHCAKRKLDGANPCEITCEELRLGHESAPEYKDFIAVAR 4100
4101 GDKKHNRRTNEPPDGLTEETQVQCLIDQATDPNILGRVWKGWEPWI 4146
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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