 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q15911 from www.uniprot.org...
The NucPred score for your sequence is 0.90 (see score help below)
1 MEGCDSPVVSGKDNGCGIPQHQQWTELNSTHLPDKPSSMEQSTGESHGPL 50
51 DSLRAPFNERLAESTASAGPPSEPASKEVTCNECSASFASLQTYMEHHCP 100
101 SARPPPPLREESASDTGEEGDEESDVENLAGEIVYQPDGSAYIVESLSQL 150
151 TQGGGACGSGSGSGPLPSLFLNSLPGAGGKQGDPSCAAPVYPQIINTFHI 200
201 ASSFGKWFEGPDQAFPNTSALAGLSPVLHSFRVFDVRHKSNKDYLNSDGS 250
251 AKSSCVSKDVPNNVDLSKFDGFVLYGKRKPILMCFLCKLSFGYVRSFVTH 300
301 AVHDHRMTLSEDERKILSNKNISAIIQGIGKDKEPLVSFLEPKNKNFQHP 350
351 LVSTANLIGPGHSFYGKFSGIRMEGEEALPAGSAAGPEQPQAGLLTPSTL 400
401 LNLGGLTSSVLKTPITSVPLGPLASSPTKSSEGKDSGAAEGEKQEVGDGD 450
451 CFSEKVEPAEEEAEEEEEEEEAEEEEEEEEEEEEEEEDEGCKGLFPSELD 500
501 EELEDRPHEEPGAAAGSSSKKDLALSNQSISNSPLMPNVLQTLSRGTAST 550
551 SSNSASSFVVFDGANRRNRLSFNSEGVRANVAEGGRRLDFADESANKDNA 600
601 TAPEPNESTEGDDGGFVPHHQHAGSLCELGVGECPSGSGVECPKCDTVLG 650
651 SSRSLGGHMTMMHSRNSCKTLKCPKCNWHYKYQQTLEAHMKEKHPEPGGS 700
701 CVYCKSGQPHPRLARGESYTCGYKPFRCEVCNYSTTTKGNLSIHMQSDKH 750
751 LNNMQNLQNGGGEQVFSHTAGAAAAAVAAAAAAANISSSCGAPSPTKPKT 800
801 KPTWRCEVCDYETNVARNLRIHMTSEKHMHNMMLLQQNMTQIQHNRHLGL 850
851 GSLPSPAEAELYQYYLAQNMNLPNLKMDSAASDAQFMMSGFQLDPAGPMA 900
901 AMTPALVGGEIPLDMRLGGGQLVSEELMNLGESFIQTNDPSLKLFQCAVC 950
951 NKFTTDNLDMLGLHMNVERSLSEDEWKAVMGDSYQCKLCRYNTQLKANFQ 1000
1001 LHCKTDKHVQKYQLVAHIKEGGKANEWRLKCVAIGNPVHLKCNACDYYTN 1050
1051 SLEKLRLHTVNSRHEASLKLYKHLQQHESGVEGESCYYHCVLCNYSTKAK 1100
1101 LNLIQHVRSMKHQRSESLRKLQRLQKGLPEEDEDLGQIFTIRRCPSTDPE 1150
1151 EAIEDVEGPSETAADPEELAKDQEGGASSSQAEKELTDSPATSKRISFPG 1200
1201 SSESPLSSKRPKTAEEIKPEQMYQCPYCKYSNADVNRLRVHAMTQHSVQP 1250
1251 MLRCPLCQDMLNNKIHLQLHLTHLHSVAPDCVEKLIMTVTTPEMVMPSSM 1300
1301 FLPAAVPDRDGNSNLEEAGKQPETSEDLGKNILPSASTEQSGDLKPSPAD 1350
1351 PGSVREDSGFICWKKGCNQVFKTSAALQTHFNEVHAKRPQLPVSDRHVYK 1400
1401 YRCNQCSLAFKTIEKLQLHSQYHVIRAATMCCLCQRSFRTFQALKKHLET 1450
1451 SHLELSEADIQQLYGGLLANGDLLAMGDPTLAEDHTIIVEEDKEEESDLE 1500
1501 DKQSPTGSDSGSVQEDSGSEPKRALPFRKGPNFTMEKFLDPSRPYKCTVC 1550
1551 KESFTQKNILLVHYNSVSHLHKLKRALQESATGQPEPTSSPDNKPFKCNT 1600
1601 CNVAYSQSSTLEIHMRSVLHQTKARAAKLEAASGSSNGTGNSSSISLSSS 1650
1651 TPSPVSTSGSNTFTTSNPSSAGIAPSSNLLSQVPTESVGMPPLGNPIGAN 1700
1701 IASPSEPKEANRKKLADMIASRQQQQQQQQQQQQQQQQQQQAQTLAQAQA 1750
1751 QVQAHLQQELQQQAALIQSQLFNPTLLPHFPMTTETLLQLQQQQHLLFPF 1800
1801 YIPSAEFQLNPEVSLPVTSGALTLTGTGPGLLEDLKAQVQVPQQSHQQIL 1850
1851 PQQQQNQLSIAQSHSALLQPSQHPEKKNKLVIKEKEKESQRERDSAEGGE 1900
1901 GNTGPKETLPDALKAKEKKELAPGGGSEPSMLPPRIASDARGNATKALLE 1950
1951 NFGFELVIQYNENKQKVQKKNGKTDQGENLEKLECDSCGKLFSNILILKS 2000
2001 HQEHVHQNYFPFKQLERFAKQYRDHYDKLYPLRPQTPEPPPPPPPPPPPP 2050
2051 LPAAPPQPASTPAIPASAPPITSPTIAPAQPSVPLTQLSMPMELPIFSPL 2100
2101 MMQTMPLQTLPAQLPPQLGPVEPLPADLAQLYQHQLNPTLLQQQNKRPRT 2150
2151 RITDDQLRVLRQYFDINNSPSEEQIKEMADKSGLPQKVIKHWFRNTLFKE 2200
2201 RQRNKDSPYNFSNPPITSLEELKIDSRPPSPEPPKQEYWGSKRSSRTRFT 2250
2251 DYQLRVLQDFFDANAYPKDDEFEQLSNLLNLPTRVIVVWFQNARQKARKN 2300
2301 YENQGEGKDGERRELTNDRYIRTSNLNYQCKKCSLVFQRIFDLIKHQKKL 2350
2351 CYKDEDEEGQDDSQNEDSMDAMEILTPTSSSCSTPMPSQAYSAPAPSANN 2400
2401 TASSAFLQLTAEAEELATFNSKTEAGDEKPKLAEAPSAQPNQTQEKQGQP 2450
2451 KPELQQQEQPEQKTNTPQQKLPQLVSLPSLPQPPPQAPPPQCPLPQSSPS 2500
2501 PSQLSHLPLKPLHTSTPQQLANLPPQLIPYQCDQCKLAFPSFEHWQEHQQ 2550
2551 LHFLSAQNQFIHPQFLDRSLDMPFMLFDPSNPLLASQLLSGAIPQIPASS 2600
2601 ATSPSTPTSTMNTLKRKLEEKASASPGENDSGTGGEEPQRDKRLRTTITP 2650
2651 EQLEILYQKYLLDSNPTRKMLDHIAHEVGLKKRVVQVWFQNTRARERKGQ 2700
2701 FRAVGPAQAHRRCPFCRALFKAKTALEAHIRSRHWHEAKRAGYNLTLSAM 2750
2751 LLDCDGGLQMKGDIFDGTSFSHLPPSSSDGQGVPLSPVSKTMELSPRTLL 2800
2801 SPSSIKVEGIEDFESPSMSSVNLNFDQTKLDNDDCSSVNTAITDTTTGDE 2850
2851 GNADNDSATGIATETKSSSAPNEGLTKAAMMAMSEYEDRLSSGLVSPAPS 2900
2901 FYSKEYDNEGTVDYSETSSLADPCSPSPGASGSAGKSGDSGDRPGQKRFR 2950
2951 TQMTNLQLKVLKSCFNDYRTPTMLECEVLGNDIGLPKRVVQVWFQNARAK 3000
3001 EKKSKLSMAKHFGINQTSYEGPKTECTLCGIKYSARLSVRDHIFSQQHIS 3050
3051 KVKDTIGSQLDKEKEYFDPATVRQLMAQQELDRIKKANEVLGLAAQQQGM 3100
3101 FDNTPLQALNLPTAYPALQGIPPVLLPGLNSPSLPGFTPSNTALTSPKPN 3150
3151 LMGLPSTTVPSPGLPTSGLPNKPSSASLSSPTPAQATMAMGPQQPPQQQQ 3200
3201 QQQQPQVQQPPPPPAAQPPPTPQLPLQQQQQRKDKDSEKVKEKEKAHKGK 3250
3251 GEPLPVPKKEKGEAPTATAATISAPLPTMEYAVDPAQLQALQAALTSDPT 3300
3301 ALLTSQFLPYFVPGFSPYYAPQIPGALQSGYLQPMYGMEGLFPYSPALSQ 3350
3351 ALMGLSPGSLLQQYQQYQQSLQEAIQQQQQRQLQQQQQQKVQQQQPKASQ 3400
3401 TPVPPGAPSPDKDPAKESPKPEEQKNTPREVSPLLPKLPEEPEAESKSAD 3450
3451 SLYDPFIVPKVQYKLVCRKCQAGFSDEEAARSHLKSLCFFGQSVVNLQEM 3500
3501 VLHVPTGGGGGGSGGGGGGGGGGGGGGSYHCLACESALCGEEALSQHLES 3550
3551 ALHKHRTITRAARNAKEHPSLLPHSACFPDPSTASTSQSAAHSNDSPPPP 3600
3601 SAAAPSSASPHASRKSWPQVVSRASAAKPPSFPPLSSSSTVTSSSCSTSG 3650
3651 VQPSMPTDDYSEESDTDLSQKSDGPASPVEGPKDPSCPKDSGLTSVGTDT 3700
3701 FRL 3703
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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