 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P13837 from www.uniprot.org...
The NucPred score for your sequence is 0.41 (see score help below)
1 MNNKFIIFSLLLALVASQTYSLTSCTCAQLLSEGDCIKNVSLGCSWDTTK 50
51 KTCGVSTTPVTPTVTYAAYCDTFAETDCPKAKPCTDCGNYAACAWVESKC 100
101 TFFTGCTPFAKTLDSECQAISNRCITDGTHCVEVDACSTYKKQLPCAKNA 150
151 AGSLCYWDTTNNTCVDANTCDKLPATFATDKDCRDVISTCTTKTGGGCVD 200
201 SGNNCSDQTLEIQCVWNKLKTTSCYWDGAACKDRICDNAPTSLTTDDACK 250
251 TFRTDGTCTTKANGGCVTRTTCAAATIQASCIKNSSGGDCYWTGTACVDK 300
301 ACANTPTTIATNSACAGFVTGCITKSGGGCVVNGACSVANVQAACVKNPS 350
351 NFDCIWDTTCKEKTCANASTTNNTHDLCTSYLSTCTVKSGGGCQNRTCAN 400
401 APTTMTTNDACEAYFTGNNCITKSGGGCVTNTTCAAITLEAACVKNSSGS 450
451 TCFWDTASSSCKDKTCVNAPATNTTHDLCQPFLNTCTVNSTSAGCVEKTC 500
501 ENSLVLAICDKDTSSRACIWKGKCYKKQCVLASSATTTHADCQTYHSTCT 550
551 LSNSGTGCVPLPLKCEAITIEAACNLKANGQPCGWNGSQCIDKACSTASK 600
601 TFTTTSQCTGHISTCVANNPVTVNGSLTIQGCQDLPTTCARRKSSENCEI 650
651 TRVGFPTCLWVSSSTSCVEKSCATASTVGTTGALSAGGFTFSGCQTYLNT 700
701 CISNNTADGCIAKPSSCSSLVSSNCRDGSKASGDCYWNGSSCVDKTCANI 750
751 IQTTHNSCNTTFNQCTVNNGGTACQTLATACTSYSTQENCKFTSTNKNCV 800
801 WTGLACRNATCADAPDTTAYDSDTECLAYPTPSETCTVVYKVGAQGCVSK 850
851 SANCSDYMTSAQCHKTLTNLTANDDCKWIVDRCYALSSFATGACTTFKGT 900
901 KTMCEGYRAGCTNTVGAASSASCTLDCTLKTGSGLTFADCQALDSTCSVK 950
951 KDGTGCIAIQSTCAGYGSTAANCFRSSASGTAGYCAMNTNCQSVTSAAEC 1000
1001 AFVTGLTGLDHSKCQLYHSSCTSLKDGTGCQEYKTTCSGYAATNNCATSG 1050
1051 QGKCFFDVECLRFSNCASITGTGLTTAICGTYDAGCVANVNGTACQEKLA 1100
1101 TCDLYLTQNSCSTSAAAATADKCAWSGTACLAVTTVGTHCPYVTGTGLTD 1150
1151 LICAAYNANCTANKAGTACQEKKATCNLYTTEATCSTSAAAATADKCAWS 1200
1201 GAACLAVTTVATECAYVTGTGLTDLICAAYNANCTANKAGTACQEKKATC 1250
1251 NLYTTEATCSTSAAAATADKCAWSGAACLAVTTVATECAYVTGTGLTNAI 1300
1301 CAAYNANCTANKAGTACQEKKATCNLYTTEATCSTSAAAATADKCAWSGA 1350
1351 ACLAVTTVATECAYVTGTGLTNAICAAYNANCTANKAGTACQEKKATCNL 1400
1401 YTTEATCSTSAAAATADKCAWSGAACLAVTTVATECAYVTGTGLTKAICA 1450
1451 TYNAGCINLKDGTGCQEAKANCKDYTTSNKCTAQTTSTLSCLWIDNSCYP 1500
1501 VTDLNCSVITGLGFVHAQCQAYSTGCTSVSDGSKCQDFKSTCEQYPGTTL 1550
1551 GCTKTASTKCYLQGSACITISNVATDCAKITGSAGTITFEICQSYNTGCS 1600
1601 VNRARSACVQQQAQCSGYTSAMTSCYKSGAGLCIASTNTDTACVAATAAT 1650
1651 CDAVYLGAGNYSSANCNEMKAGCTNNGTTACVAKTCANAAGITFNHTNCN 1700
1701 SYLNTCTVNSGNSACQTMASKCADQTQASCLYSVEGECVVVGTSCVRKTC 1750
1751 DTAATDATRDDDTECSTYQQSCTVARLGACQARAACATYKSSLQCKFNTS 1800
1801 GGKCFWNPTNKTCVDLNCGNIEATTLYDTHNECVAVDATLACTVRATNGA 1850
1851 AAQGCMARGACASYTIEEQCKTNASNGVCVWNTNANLPAPACQDKSCTSA 1900
1901 PTSTTTHNDCYAYYNTATVKCTVVATPSNSGGNPTLGGCQQTAACSSYID 1950
1951 KEQCQINANGDPCGWNGTQCADKSCATASATADYDDDTKCRAYITNKCTV 2000
2001 SDSGQGCVEIPATCETMTQKQCYYNKAGDPCYWTGTACITKSCDNAPDAT 2050
2051 ATADECNTYLAGCTLNNVKCKTKVCEDFAFATDALCKQAISTCTTNGTNC 2100
2101 VTRGTCFQALSQAGCVTSSTNQQCEWIPAVLNASNVITSPAYCTIKNCST 2150
2151 APITLTSEAACAGYFTNCTTKNGGGCVTKSTCSAVTIDVACTTALNGTVC 2200
2201 AWDSAQNKCRDKDCQDFSGTTHAACQAQRAGCTAGAGGKCARVQNCEQTS 2250
2251 VRAACIEGTNGPCLWIDKYQNTDGTKGACFRYTSCKSLNWNNDSSCKWIS 2300
2301 NKCTTNGSNCVGITLCSETNTDGGCVTGYDGACIQSVPDLNSSDPKVCKP 2350
2351 YTSCADAFYTTHSDCQIASSKCTTNGTTGCIALGSCSSYTVQAGCYFNDK 2400
2401 GTLYTSGVITSTGICTWDTTSSSCRDQSCADLTGTTHATCSSQLSTCTSD 2450
2451 GTTCLLKGACTSYTTQTACTTAVGSDGACYWELASATNNNTAKCRLLTCA 2500
2501 DIQNGTATNVCSVALSTCVSNGTACIPKANCSTYTSKVACNSGGLDGICV 2550
2551 FTQSTATGAAAGTGTCALMTACTVANNDQTACQAARDRCSWTAASGTRAT 2600
2601 AVASKCATHTCATNQATNGACTRFLNWDKKTQQVCTLVSGACTATDPSSF 2650
2651 SSNDCFLVSGYTYTCNASTSKCGVCTAVVVQPNTTDNNTNTTDNNTTTDS 2700
2701 GYILGLSIVLGYLMF 2715
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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