 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P17053 from www.uniprot.org...
The NucPred score for your sequence is 0.29 (see score help below)
1 MNNKFIIFSLLLALVASQTYSLTSCTCAQLLSEGDCIKNVSLGCSWDTTK 50
51 KTCGVSTTPVTPTVTYAAYCDTFAETDCPKAKPCTDCGNYAACAWVESKC 100
101 TFFTGCTPFAKTLDSECQAISNRCITDGTHCVEVDACSTYKKQLPCVKNA 150
151 AGSLCYWDTTNNTCDKLPATFATDKDCRDVISTCTTKTGGGCVDSGNNCS 200
201 DQTLEIQCVWNKLKTTSCYWDGAACKDRICDNAPTSLTTDDACKTFRTDG 250
251 TCTTKANGGCVTRTTCAAATIQASCIKNSSGGDCYWTGTACVDKTCANAP 300
301 TTMTTNSACAGFVTGCITKSGGGCVANGACSVANVQAACVKNSSNFDCIW 350
351 DTTCKEKTCANAPTTNNTHDLCTSYLSTCTVKSGGGCQNRSCANAPTTMT 400
401 TNDACEAYLTGNNCITKSGGGCVTNTTCAAITLEAACVKNSSGSTCFWDT 450
451 ASSSCKDKTCVNAPATNTTHDLCQAFLNTCTVNSTSAGCVEKTCENSLVL 500
501 AICDKDTSSRACIWKGKCYKKQCVLASSATTTHADCQTYHSTCTLSNSGT 550
551 GCVPLPLKCEAITIEAACNLKANGQPCGWNGSQCIDKACSTASKTFTTTS 600
601 QCTGHISTCVANNPVTVNGSLTIQGCQDLPTSCAARKSSENCEIARVGFP 650
651 TCLWVSSSTSCVEKSCATASTVGTTGALSAGGFTFSGCQTYLNTCISNNT 700
701 ADGCIAKPSSCSSLVSSNCRDGSKASGDCYWNGSSCVDKTCANITLTSHA 750
751 SCYSIFNQCTVNNGGTACQTLATACTSYSTQENCKFTSTNKNCVWTGLAC 800
801 RNATCADAPDTTAYDSDTECLAYPTPSETCTVVYKVGAQGCVSKSANCSD 850
851 YMTSAQCHKTLTNLTANDDCKWIVDRCYALSSFATGACTTFKGNKTMCEG 900
901 YRAGCTNTVGAASSASCTLDCTLKTGSGLTFADCQALDSTCSVKKDGTGC 950
951 IVIQSTCAGYGSTATNCFRSSASGTAGYCAMNTNCQSVTSAAECAFVTGL 1000
1001 TGLDHSKCQLYHSSCTSLKDGTGCQEYKTACSSYATGNTCANSVQGKCFD 1050
1051 DATDCLRFANCASITGTGLTNTICVTYDPGCVANVNGTACQEKLATCAAY 1100
1101 LTQNSCSTSTAGTCAWSGSACLTVVDANVATECAYITGTGLTNAICAGYN 1150
1151 AKCTVNRAGTACQKKEALCATYAAVQATCSQSDAGLCAWSGSACLTVVDA 1200
1201 NVATECPYITGTGLTNAICAGYNAKCTVNRAGTACQKKEALCATYAAVQA 1250
1251 TCSQSDAGLCAWSGSACLTVVDANVATECPYITGTGLTDAICAGYNAKCT 1300
1301 VNRAGTACQKKEALCATYAAVQATCSQSDAGLCAWSGSACLTVVDANVAT 1350
1351 ECPYITGTGLTNAICAGYNAKCTVNRAGTACQKKEALCATYAAVQATCSQ 1400
1401 SDAGLCAWSGSACLTVVDANVATECAYITGTGLTDAICAGYNAKCTNLKD 1450
1451 GTGCQDEKATCKLYTTQNKCTSQTTGPLSCLWFDNSCSPITDVTCSAIVQ 1500
1501 SGLDHAQCQAYSTGCTSVSDGSKCQDFKTTCEQYAGTALSCTKTATSKCY 1550
1551 LQGSNCITISNVATDCAKITGSAGTITYEICQSYNTGCSVNRARSACVQQ 1600
1601 QAQCSGYTSAMTSCYKSGAGLCIASTNTDTACVAATAATTCDAVYLGTGN 1650
1651 YSSANCNEMKAGCTNNGATACVAKTCANAVVIFNHTNCNGYLNTCTVNSG 1700
1701 NSACQTMASKCADQTQASCLYSVEGECVVVGTSCVRKTCDTAATDATRDD 1750
1751 DTECSAYQQSCTVARLGACQARAACASYKSSLQCKFNTSGGRCFWNPTNK 1800
1801 TCVDLNCGNIEASTLYDTHNECVVVDATLACTVRATNGAAVQGCMARGAC 1850
1851 SSYTIEEQCKTNASNGVCVWNTNANLPAPACQDKSCTSAPTSTTTHNDCY 1900
1901 AYYNTATVKCTVVATPSNSGGNPTLGGCQQTAACSSYIDKEQCQINANGE 1950
1951 PCGWNGTQCADKSCATAPATADYDDDTKCRAYITNKCTVSDSGQGCVEIP 2000
2001 ATCETMTQKQCYYNKAGDPCYWTGTACITKSCDNAPDATATADECNTYLA 2050
2051 GCTLDNVKCKTKVCEDFAFATDALCKQAISTCTTNGTNCVTRGTCFQALS 2100
2101 QAGCVTSSTNQQCEWIPAVLNASNVITSPAYCTIKNCSTAPITLTSEAAC 2150
2151 AGYFTNCTTKNGGGCVTKSTCSAVTIDVACTTALNGTVCAWDSAQNKCRD 2200
2201 KDCQDFSGTTHAACQAQRAGCTAGASGKCARVQNCEQTSVRAACIEGTNG 2250
2251 PCLWIDKYQNTDGTKGACFRYTSCKSLNWNNDSSCKWISNKCTTNGSNCV 2300
2301 GITLCSETNTDGGCVTGYDGACIQSVPALNSSDPKVCKPYTSCADAFYTT 2350
2351 HSDCQIASSKCTTNGTTGCIALGSCSSYTAQAGCYFNDKGTLYTSGVITS 2400
2401 TGICTWDTTSSSCRDQSCADLTGTTHATCSSQLSTCTSDGTTCLLKGACT 2450
2451 SYTTQTACTTAVGSDGACYWELASATNNNTAKCRLLTCADIQNGTATNVC 2500
2501 SVALSTCVSNGTACIPKANCSTYTSKIACNSGGLDGICVFTQSTATGAAA 2550
2551 GTGTCALMTACTVANNDQTACQAARDRCSWTAASGTGATAVASKCATHTC 2600
2601 ATNQATNGACTRFLNWDKKTQQVCTLVSGACTATDPSTLSSNDCFLVSGY 2650
2651 TYTWNASTSKCGVCTAVVVQPNTTDNNTNTTDNNTTTDSGYILGLSIVLG 2700
2701 YLMF 2704
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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