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

NucPred

Fetching Q01118 from www.uniprot.org...

The NucPred score for your sequence is 0.40 (see score help below)

   1  MLASPEPKGLVPFTKESFELIKQHIAKTHNEDHEEEDLKPTPDLEVGKKL    50
  51  PFIYGNLSQGMVSEPLEDVDPYYYKKKNTFIVLNKNRTIFRFNAASILCT   100
 101  LSPFNCIRRTTIKVLVHPFFQLFILISVLIDCVFMSLTNLPKWRPVLENT   150
 151  LLGIYTFEILVKLFARGVWAGSFSFLGDPWNWLDFSVTVFEVIIRYSPLD   200
 201  FIPTLQTARTLRILKIIPLNQGLKSLVGVLIHCLKQLIGVIILTLFFLSI   250
 251  FSLIGMGLFMGNLKHKCFRWPQENENETLHNRTGNPYYIRETENFYYLEG   300
 301  ERYALLCGNRTDAGQCPEGYVCVKAGINPDQGFTNFDSFGWALFALFRLM   350
 351  AQDYPEVLYHQILYASGKVYMIFFVVVSFLFSFYMASLFLGILAMAYEEE   400
 401  KQRVGEISKKIEPKFQQTGKELQEGNETDEAKTIQIEMKKRSPISTDTSL   450
 451  DVLEDATLRHKEELEKSKKICPLYWYKFAKTFLIWNCSPCWLKLKEFVHR   500
 501  IIMAPFTDLFLIICIILNVCFLTLEHYPMSKQTNTLLNIGNLVFIGIFTA   550
 551  EMIFKIIAMHPYGYFQVGWNIFDSMIVFHGLIELCLANVAGMALLRLFRM   600
 601  LRIFKLGKYWPTFQILMWSLSNSWVALKDLVLLLFTFIFFSAAFGMKLFG   650
 651  KNYEEFVCHIDKDCQLPRWHMHDFFHSFLNVFRILCGEWVETLWDCMEVA   700
 701  GQSWCIPFYLMVILIGNLLVLYLFLALVSSFSSCKDVTAEENNEAKNLQL   750
 751  AVARIKKGINYVLLKILCKTQNVPKDTMDHVNEVYVKEDISDHTLSELSN   800
 801  TQDFLKDKEKSSGTEKNATENESQSLIPSPSVSETVPIASGESDIENLDN   850
 851  KEIQSKSGDGGSKEKIKQSSSSECSTVDIAISEEEEMFYGGERSKHLKNG   900
 901  CRRGSSLGQISGASKKGKIWQNIRKTCCKIVENNWFKCFIGLVTLLSTGT   950
 951  LAFEDIYMDQRKTIKILLEYADMIFTYIFILEMLLKWMAYGFKAYFSNGW  1000
1001  YRLDFVVVIVFCLSLIGKTREELKPLISMKFLRPLRVLSQFERMKVVVRA  1050
1051  LIKTTLPTLNVFLVCLMIWLIFSIMGVDLFAGRFYECIDPTSGERFPSSE  1100
1101  VMNKSRCESLLFNESMLWENAKMNFDNVGNGFLSLLQVATFNGWITIMNS  1150
1151  AIDSVAVNIQPHFEVNIYMYCYFINFIIFGVFLPLSMLITVIIDNFNKHK  1200
1201  IKLGGSNIFITVKQRKQYRRLKKLMYEDSQRPVPRPLNKLQGFIFDVVTS  1250
1251  QAFNVIVMVLICFQAIAMMIDTDVQSLQMSIALYWINSIFVMLYTMECIL  1300
1301  KLIAFRCFYFTIAWNIFDFMVVIFSITGLCLPMTVGSYLVPPSLVQLILL  1350
1351  SRIIHMLRLGKGPKVFHNLMLPLMLSLPALLNIILLIFLVMFIYAVFGMY  1400
1401  NFAYVKKEAGINDVSNFETFGNSMLCLFQVAIFAGWDGMLDAIFNSKWSD  1450
1451  CDPDKINPGTQVRGDCGNPSVGIFYFVSYILISWLIIVNMYIVVVMEFLN  1500
1501  IASKKKNKTLSEDDFRKFFQVWKRFDPDRTQYIDSSKLSDFAAALDPPLF  1550
1551  MAKPNKGQLIALDLPMAVGDRIHCLDILLAFTKRVMGQDVRMEKVVSEIE  1600
1601  SGFLLANPFKITCEPITTTLKRKQEAVSATIIQRAYKNYRLRRNDKNTSD  1650
1651  IHMIDGDRDVHATKEGAYFDKAKEKSPIQSQI                    1682

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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