SBC logo Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden.

NucPred

Fetching Q61555 from www.uniprot.org...

The NucPred score for your sequence is 0.64 (see score help below)

   1  MGRRRRLCLQPYFVWLGCVALWAQGTDGQPQPPPPKTLRPQPPPQQVRPA    50
  51  VAGSEGGFMGPEYRDEGAVAASRVRRRGQQEILRGPNVCGSRFHSYCCPG   100
 101  WKTLPGGNQCIVPICRNSCGDGFCSRPNMCTCSSGQISPTCGAKSIQQCS   150
 151  VRCMNGGTCADDHCQCQKGYIGTYCGQPVCENGCQNGGRCIGPNRCACVY   200
 201  GFTGPQCERDYRTGPCFTQVNNQMCQGQLTGIVCTKTLCCATIGRAWGHP   250
 251  CEMCPAQPQPCRRGFIPNIRTGACQDVDECQAIPGLCQGGNCINTVGSFE   300
 301  CRCPAGHKQSETTQKCEDIDECSVIPGVCETGDCSNTVGSYFCLCPRGFV   350
 351  TSTDGSRCIDQRAGTCFSGLVNGRCAQELPGRMAKAQCCCEPGRCWSIGT   400
 401  IPEACPVRGSEEYRRLCLDGLPMGGIPGSSVSRPGGTGSTGNGYGPGGTG   450
 451  FLPIPGDNGFSPGVGGAGVGAGGQGPIITGLTILNQTIDICKHHANLCLN   500
 501  GRCIPTVSSYRCECNMGYKQDANGDCIDVDECTSNPCSNGDCVNTPGSYY   550
 551  CKCHAGFQRTPTKQACIDIDECIQNGVLCKNGRCVNTDGSFQCICNAGFE   600
 601  LTTDGKNCVDHDECTTTNMCLNGMCINEDGSFKCVCKPGFILAPNGRYCT   650
 651  DVDECQTPGICMNGHCINNEGSFRCDCPPGLAVGVDGRVCVDTHMRSTCY   700
 701  GEIKKGVCVRPFPGAVTKSECCCANPDYGFGEPCQPCPAKNSAEFHGLCS   750
 751  SGIGITVDGRDINECALDPDICANGICENLRGSYRCNCNSGYEPDASGRN   800
 801  CIDIDECLVNRLLCDNGLCRNTPGSYSCTCPPGYVFRTETETCEDVNECE   850
 851  SNPCVNGACRNNLGSFHCECSPGSKLSSTGLICIDSLKGTCWLNIQDNRC   900
 901  EVNINGATLKSECCATLGAAWGSPCERCELDAACPRGFARIKGVTCEDVN   950
 951  ECEVFPGVCPNGRCVNSKGSFHCECPEGLTLDGTGRVCLDIRMEHCFLKW  1000
1001  DEDECIHPVPGKFRMDACCCAVGAAWGTECEECPKPGTKEYETLCPRGPG  1050
1051  FANRGDILTGRPFYKDINECKAFPGMCTYGKCRNTIGSFKCRCNNGFALD  1100
1101  MEERNCTDIDECRISPDLCGSGICVNTPGSFECECFEGYESGFMMMKNCM  1150
1151  DIDECERNPLLCRGGTCVNTEGSFQCDCPLGHELSPSREDCVDINECSLS  1200
1201  DNLCRNGKCVNMIGTYQCSCNPGYQATPDRQGCTDIDECMIMNGGCDTQC  1250
1251  TNSEGSYECSCSEGYALMPDGRSCADIDECENNPDICDGGQCTNIPGEYR  1300
1301  CLCYDGFMASMDMKTCIDVNECDLNPNICMFGECENTKGSFICHCQLGYS  1350
1351  VKKGTTGCTDVDECEIGAHNCDMHASCLNVPGSFKCSCREGWVGNGIKCI  1400
1401  DLDECANGTHQCSINAQCVNTPGSYRCACSEGFTGDGFTCSDVDECAENT  1450
1451  NLCENGQCLNVPGAYRCECEMGFTPASDSRSCQDIDECSFQNICVFGTCN  1500
1501  NLPGMFHCICDDGYELDRTGGNCTDIDECADPINCVNGLCVNTPGRYECN  1550
1551  CPPDFQLNPTGVGCVDNRVGNCYLKFGPRGDGSLSCNTEVGVGVSRSSCC  1600
1601  CSLGKAWGNPCETCPPVNSTEYYTLCPGGEGFRPNPITIILEDIDECQEL  1650
1651  PGLCQGGNCINTFGSFQCECPQGYYLSEETRICEDIDECFAHPGVCGPGT  1700
1701  CYNTLGNYTCICPPEYMQVNGGHNCMDMRKSFCYRSYNGTTCENELPFNV  1750
1751  TKRMCCCTYNVGKAWNKPCEPCPTPGTADFKTICGNIPGFTFDIHTGKAV  1800
1801  DIDECKEIPGICANGVCINQIGSFRCECPTGFSYNDLLLVCEDIDECSNG  1850
1851  DNLCQRNADCINSPGSYRCECAAGFKLSPNGACVDRNECLEIPNVCSHGL  1900
1901  CVDLQGSYQCICNNGFKASQDQTMCMDVDECERHPCGNGTCKNTVGSYNC  1950
1951  LCYPGFELTHNNDCLDIDECSSFFGQVCRNGRCFNEIGSFKCLCNEGYEL  2000
2001  TPDGKNCIDTNECVALPGSCSPGTCQNLEGSFRCICPPGYEVRSENCIDI  2050
2051  NECDEDPNICLFGSCTNTPGGFQCICPPGFVLSDNGRRCFDTRQSFCFTN  2100
2101  FENGKCSVPKAFNTTKAKCCCSKMPGEGWGDPCELCPKDDEVAFQDLCPY  2150
2151  GHGTVPSLHDTREDVNECLESPGICSNGQCINTDGSFRCECPMGYNLDYT  2200
2201  GVRCVDTDECSIGNPCGNGTCTNVIGSFECTCNEGFEPGPMMNCEDINEC  2250
2251  AQNPLLCAFRCMNTFGSYECTCPVGYALREDQKMCKDLDECAEGLHDCES  2300
2301  RGMMCKNLIGTFMCICPPGMARRPDGEGCVDENECRTKPGICENGRCVNI  2350
2351  IGSYRCECNEGFQSSSSGTECLDNRQGLCFAEVLQTMCQMASSSRNLVTK  2400
2401  SECCCDGGRGWGHQCELCPLPGTAQYKKICPHGPGYATDGRDIDECKVMP  2450
2451  SLCTNGQCVNTMGSFRCFCKVGYTTDISGTACVDLDECSQSPKPCNFICK  2500
2501  NTKGSYQCSCPRGYVLQEDGKTCKDLDECQTKQHNCQFLCVNTLGGFTCK  2550
2551  CPPGFTQHHTACIDNNECGSQPSLCGAKGICQNTPGSFSCECQRGFSLDA  2600
2601  SGLNCEDVDECDGNHRCQHGCQNILGGYRCGCPQGYVQHYQWNQCVDENE  2650
2651  CSNPGACGSASCYNTLGSYKCACPSGFSFDQFSSACHDVNECSSSKNPCS  2700
2701  YGCSNTEGGYLCGCPPGYFRVGQGHCVSGMGFNKGQYLSVDAEAEDDENA  2750
2751  LSPEACYECKINGYTKKDGRRKRSAQEPEPASAEEQISLESVAMDSPVNM  2800
2801  KFNLSGLGSKEHILELVPAIEPLNNHIRYVISQGNEDGVFRIHQRNGLSY  2850
2851  LHTAKKKLAPGTYTLEITSIPLYGKKELRKLEEHNEDDYLLGVLGEALRM  2900
2901  RLQIQLY                                             2907

Positively and negatively influencing subsequences are coloured according to the following scale:

(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)

with NucPred



If you find NucPred useful, please cite this paper:
NucPred - Predicting Nuclear Localization of Proteins. Brameier M, Krings A, Maccallum RM. Bioinformatics, 2007. PubMed id: 17332022
The authors also look forward to your comments and suggestions.

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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