| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q1KXP6 from www.uniprot.org...
The NucPred score for your sequence is 0.98 (see score help below)
1 MTGHEFKSWILELREILREIKNSHYFLDSWTQFNSVGSFIHIFFHQERFI 50
51 KLFDSRIWSILLSHNSQGSTSNRYFTIKGVILFGVAVLIYRINNRNMVER 100
101 KNLYLIGLLPIPMNSIGPRNDTLEESVGSSNINRLIVSLLYLPKGKKIYE 150
151 SSFLNPKESTWVLPITKKCSMPESNWGSRWWRDWIGKKSDSSCKISNETV 200
201 AGIEILFKEKDLKYLEFVFVYYRDDPIRKDHGWEFFDRLSLRKRQNRINL 250
251 NSGPLFEILVKHWICYLMSAFREKIPIEVEGFFKQQGAGSTIQSNDIEHV 300
301 SHLFSRNKSRLFTEREKQMINHMLPEEIEEFLGNPTRSVRSFFSDRWSEL 350
351 HLGSNPTERSTRDQKLLKKQQDLSFLRRSEKKEMVNLFKIITYLQNTVSI 400
401 HPISLDSGCDMVPKDEPDMDSSNKISFLNKNPFFDLFHLFHDRNRGGYTL 450
451 HHDFESEDRFQEMADLFTLSITEPDLVYHKRFAFSIDSYGLDPKQFLNGV 500
501 FNSRYEWKTTSLLVLFPIFYEENESFYRRIRKNRVRISCGNDLEEPKPKI 550
551 VVFASNNIMEAVNQYRLIRNLIQIQHSTHRYIRNVLNRFFLMNRSDRNFE 600
601 YGIQRDQIRKDTLNHRTLMKYTINQHLSNLKKSQKRWFDPLIFFYRTERS 650
651 MNRDPDAYRYKWSTGSNNFQEHLEHFVSEQKSRLQVVFDRLRINPYSIDW 700
701 SEVIDKKDLSKPLRFFLSKLLLFLSNSLPFLFVSFGNIPIHRSEIYIYQL 750
751 KGPNDPQFLESIGLQIVHLKKLKPFLLDDHETCQKSKFLINGGTISPFLF 800
801 NKIPKWMIDSFHTRNNRRKSFDNTDSYFSMIFHDQYNWLNPVKSFHRSSL 850
851 RSSFYKGNQLRFLNNPHHFCFYCNKRFPFYVEKARINNYDFTYGQFLNIL 900
901 FIRNKIFSLCVGKKKHAFWGRDTISAIESQVSNIFIPKAFPQSGDETYNL 950
951 YKSFHFPSRSNPFVRRAIYSIADISGTPLTEGQIVNFERTYCQPLSDMNL 1000
1001 SDSEGKNLYQYLNFNSNMGLIHTPCSEKYLPSEKRKKRSLCLKKCVEKGQ 1050
1051 MYRTFQRDSAYSTLSKWNLFQTYMPWFLTSTGYRYLKFLFLDTFSDLLPI 1100
1101 LSSSQKFVSIFHDIMHGSDISWRILQKKFCLPQWNLISEISSKCFHNLLL 1150
1151 SEEMIHRNNESPLISTHLTNVREFLYAILFLLLVAAYLVCTHLLFVFGAS 1200
1201 SELQAEFEKVKSLMIPSSMIELRKILDRYPTSEPNSFWLKNLFLVALKQL 1250
1251 GDSLGGNMLLGGGPAYGVKSIRSKKKYLNINLIDIIDLISIIPNPINRIT 1300
1301 FSRNTRHLSHTSKEIYSLIRKRKNVNGDWIDDKIESWVANSDSIDDEKRE 1350
1351 FLVQFSTLTTEKRIDQILLSLTHSDHLSKNDSGYQMIEQPGAIYLRDLVD 1400
1401 IHKKYLMNYEFNTSSLAERRIFLAHYQTITYSQTSCGANSFHFPSHGKPF 1450
1451 SLRLALSLSRGILVIGSIGTGRSYLVKYLAKNSYLPFITVFLNKFLDNKS 1500
1501 QGFDDIDIDDLDASDDLDASDDLDASDDLDASDDILDMELELLTSMNALT 1550
1551 MNMMPEDEDQLYITLQFELAKAMSPCIIWIPNIHDLDVNESNYFSLGLLV 1600
1601 NLLSRDYETRNILVIASTHIPQKVDPALIAPNKLNTCIKIRRLLIPQQRK 1650
1651 HFFTLSYTRGFHLEKKMFHTNGFGSITMGSNARDLVALTNEALSISITQK 1700
1701 KSIIDTNTIRSALHRQIWDLRSQVRSVQDHGILFYQIGRAVAQNVLLSNC 1750
1751 PIDPISIYMKKKSCNEVDFYLYNWYFELGTSMKKLTILLYLLSCSAGSVT 1800
1801 QDLWSLPGPDEKNGITPYGLVENDSGLVRGLLEVEGALVGSSRTCSQFDK 1850
1851 DRVTLLLRPEPRNPLDMMQKGSCSILDQRFLYEKDESEFEEGEGALDRQQ 1900
1901 IEEDLFNHIVWAPRIWRPWGFLFDCIERPNELGFPYWSRSFRGKRIIYDK 1950
1951 EDELQENDSEFLQSGTAQYQTRDRSSKEQGLFRISQFIWDPADPLFFLFK 2000
2001 AQPFVSVFSHRELFADEEMSKGLLTPQTNPPTSLYKRWFIKKTQEKHFEL 2050
2051 LINRQRWLRTNRSLSNGSFRSNTLSESYQYLSNLFLSNGTLLDQMTKALL 2100
2101 RKRWLFPDEMQIGFMEQEKDFPFLSRKDMWP 2131
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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