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

NucPred

Fetching Q9QZC2 from www.uniprot.org...

The NucPred score for your sequence is 0.69 (see score help below)

   1  MEVSRRKTPPRPPYPAAPLPLIAYLLALAAPARGADEPVWRSEQAIGAIA    50
  51  ASRADGVFVASGSCLDQLDYSLKNRLSRLYRDQAGNCTEPVSLAPPARPR   100
 101  PGSSFSKLLLPYREGATGLEGLLLTGWTFDRGACEVRPLGNLNRSSLRNG   150
 151  TEVVSCHPQGSTAGVVYRASGTDLWYLAVAATYVLPEPETANRCNPAASD   200
 201  RDTAIALKNTEGRSLATQELGRLKLRGSAGSLHFVDAFLWNGSVYFPYYP   250
 251  YNYTSGAATGWPSMARIAQSTEVLFQGQAALDCDHGHPEGRRLLLSSSLV   300
 301  EAVDIWAGVFSAATGEGQERRSPATTALCLFRMSEIQAHARSCSWDFQAT   350
 351  EHNCKEGDRPERVQPIASSTLIHSDLTSVYGTVVMNRTVLFLGTGDGQLL   400
 401  KVVLGENLTSNCPEVIYEIKEETPVFYKLVPHPMKNIYIYLTAGKEVRRI   450
 451  PVANCSKRKSCSECLAAADPHCGWCLPLQRCTFQGDCTHAGSFENWLDIS   500
 501  SGPKKCPKIQILRSLRERTTVTIVGSISARHSECVVKNADTGKLLCQGRS   550
 551  QLNWTCACNIPSRPSYNVLVVNATFSFPSWNLSERFNFTNCASLKECPAC   600
 601  IRSGCAWCKRDKKCIHPFTPCEPSDYERNQELCQVAVEKSPKDSGGGRVK   650
 651  ESKRNRTDGAVQVFYIKAIEPQKISTLGKSNVIVTGANFTQASNITMILR   700
 701  GTSTCERDVIRVSHVLNDTHMKFSLPSSRKEMKDVCIQFDGGTCSSAGAL   750
 751  SYIALPHCSLIVPATTWISGGQNITIMGRNFDVIDNLIISHELKGNANVN   800
 801  INVSEYCAATFCRFLAPNLKSSKVRTNVAVKLRVQDTYLDCGTLQYLEDP   850
 851  RFTGYRVESEIDTELEVKIQKENDNFNISKDDIDITLFHGENKQFNCSFE   900
 901  NITRNQDLTTILCKIKSIKNANTIASSSKKVRVKLGNLELYVEQESVPST   950
 951  WYFLIALPILLAIVIVVAVVVTRYKSKELSRKQSQQLELLESELRKEIRD  1000
1001  GFAELQMDKLDVVDSFGTVPFLDYKHFALRTFFPESGGFTHIFTEDMHNR  1050
1051  DANDKNESLTALDALICNKSFLVTVIHTLEKQKNFSVKDRCLFASFLTIA  1100
1101  LQTKLVYLTSILEVLTRDLMEQCSNMQPKLMLRRTESVVEKLLTNWMSVC  1150
1151  LSGFLRETVGEPFYLLVTTLNQKINKGPVDVITCKALYTLNEDWLLWQVP  1200
1201  EFNTVALNVVFEKIPENESADVCRNISVNVLDCDTIGQAKEKVFQAFLSK  1250
1251  NGSPYGLQLNEIGLELQVGTRQKELLDIDSSSVILEDGITKLNTIGHYEI  1300
1301  SNGSTIKVFKKIANFTSDVEYSDDHCHLILPDSEAFQVVQGKRHRGKHKF  1350
1351  KVKEMYLTKLLSTKVAIHSVLEKLFRSIWSLPNSRAPFAIKYFFDFLDAQ  1400
1401  AENKKITDPDVVHIWKTNSLPLRFWVNILKNPQFVFDIKKTPHIDSCLSV  1450
1451  IAQAFMDAFSLTEQQLGKEAPTNKLLYAKDIPTYKEEVKSYYKAIRDLPP  1500
1501  LSSLEMEEFLTQESKKHENEFNEEVALTEIYKYIVKYFDEILNKLERERG  1550
1551  LEEAQKQLLHVKVLFDEKKKCKWM                            1574

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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