 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P16355 from www.uniprot.org...
The NucPred score for your sequence is 0.77 (see score help below)
1 MSGIAFVEVRTRAGQEDRSAPWRPVVRNGENHATFYDTRMGNFDANPFPP 50
51 QTCQTCAASLTGKYGNERCHGHFGFVGMPRIRPGSAHSDSDRLVVLNPHL 100
101 AMDADRLFRAKCFFCHKFRAPTFDVERFRQALVLADHGLPGDALHLLDTV 150
151 PTAKGHDAMLNHRRMANEEIVNDVSILQSYVDRILRQRASGCSEEDAKAR 200
201 VTMAQKGTVDVRNDICNMAISHLRSFSGPCSHCTAISPTFLKRGGIIFFL 250
251 FRKSNLVTNIAKGFLTQQEVSEWEAVNRLHGRTGTYFDGRQMLFHMKNLF 300
301 AKEQAILGLLYPNLGEPSVFTKTNKVVPASERYKLFFLDRILVPPLPLRL 350
351 SSGVRVNDNGLIIPDEQTRALSDILGFVEQIECFHTLSANSTNGRSFITD 400
401 AQRAVNESNLRNLQQKVDEFYAEIVNSFAKKEGLFRMNMMGKRVNQACRS 450
451 VISPDPFVEPNEVLLPRPLARALSFPEQVTCFAPARMNLLKHCVVNGPRK 500
501 YPGATHIELRHANGEIRSVDLNVPEQTRRQHAARFFAMAQSGVTLIVYRH 550
551 ILNGDRVIFNRQPTLHKPSMMGYRVKVLSGSKTIRFHYVNGNSFNADFDG 600
601 DEMNVHVPQSIETRAEVETLMDANINYLVPTSGRPIRGLIQDHVAAGVLV 650
651 TLRDKFFDHSTFVQLVYNGVGPYIQENVGITLAELIPIPAILMPRPMWTG 700
701 KQLISVMVRFSSGLSAASDCGREIEGGITLKGTSQIQPSAFDRIPAGSCD 750
751 AVRAKSGAVVDSTVMFANSELITGFMCKKQLGASNMSAPHHVYELYGPHR 800
801 TGQLFAAFGRVLLLALRKEGLSLAMDDMFLVDEERRCDLLRKLDDIALDV 850
851 PDEEATAAPMIADYATKIQQEFVPQRMLVPFPKNHLLLMTISGAKGSNLN 900
901 ATQMSLQLGQQLFDGLRVKRMNSSKTLPSFFTNEKRARSFGFAMGSFASG 950
951 IRPAEYTIHAMAGRDGLIDTAVKTSRSGHLQRCLIKGLESLVVHWDRTVR 1000
1001 DSNGSVIQFMYGGDGLDPCKASTLTAWEMMKDNVVDVSKRFGGDASESVA 1050
1051 GAEDGAAAGLKEMRNEDGKPTTEAVQNAHMEQQLSTYPLPASLDKSLSEY 1100
1101 LCKKADFPLFRKVSTLARWDAKQQLKERLQQRRQKWVGAFEKTLADITAR 1150
1151 RRLWALCEPGEPVGLLAAQAAGEPSTQMTLNTFHTAGSTVSHVTEGIPRL 1200
1201 RELLIYASVNKAAVVVPVTNATEEDEKVIAKMLRAGVAAKLTDCLAKVTD 1250
1251 GAGGQSASSSMQRNLNTGFGKGYHYHVARGRTGMVITVSFLFSRSCLEEL 1300
1301 RKRMCMSPSEHRQSFTEALKNVVRLIMRSLSAVPREKESGDGSGNTGGMK 1350
1351 GGSGRADRKRKRSGPDDGGGPLGGTFGDEIMRIEEGTDSDDGMSERSSIG 1400
1401 GGRAGSEVSSLHSDGTDTRGIAGSDTGGPQRRRGSVESGRGDDASDSEAA 1450
1451 DPDLYARRSGSPARDAEDGGEMQDRDGTDWGGTSMQGVVGYDNFPEIHMS 1500
1501 FTKSNFGAVIAPLSTAAAARDGVVQLHEDFFIVNAVLRTASDVIAVIPDV 1550
1551 VDNALEAQRMPSWLPQFGSLTFTRLKDKGSGQLVFQGPGSTMRNVMSFLS 1600
1601 LFTVGIKSIKLHQACSTDIRDMGTYFGIESGYAALYDELNKLFNRYNVDP 1650
1651 RHLSLIADTSTHRGRWENFNFTGVISTSASPLFQMTFASSKRWLHRAVSR 1700
1701 GMSDDLESFSSAIMVGERPRVGTASVRLSTDTAILRDVLERNFA 1744
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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