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

NucPred

Fetching Q6BGY8 from www.uniprot.org...

The NucPred score for your sequence is 0.99 (see score help below)

   1  MNISSMLSNDSNTASQDVGGNFDDSQRNNDKGGSQDANSKKMGTGEAEDH    50
  51  ANGNASVEGNGIANHGSATNGNTKGTDDSSNVNIVESIIPKPIRPTRSSI   100
 101  ESDEEDVGKNYNSIISNDSEHISQRYLENFEDKVNAINKIDQVLIKGNNM   150
 151  RVLNQEEENLNILIRNSGEIAENYIDRVVTEDISSKANILNGKDSVGKEF   200
 201  KWGSTRDMKKRELELEVDNASKADTAAKKGGNKSKQGATKSTPAKKAKAK   250
 251  PKRKPSATDDTSEESQLGKKRKTRAGSVSGASQNDEKSANGKVKLKLTLK   300
 301  DQAEEDSASADAASKVTTKEQKIITKQYDNTFVSIWKDLSRKDGPKVSRL   350
 351  MQQSTQAKMINLKKTSILAAREAKRWQLKNNRNQKDLTTKARRAMREMFN   400
 401  FWKRNERIERELRKKHEKEILDKAKKEEEERESKRQSRKLNFLITQTELY   450
 451  SHFIGKKIKTDEFEGTDSDPNANFKSANHHYDKYSNIDGEGKDFNSIDFD   500
 501  NEDEESLNKAAAVNAQIALEAAKTKAQAFDNDPLKNPDTNGEEMNFQNPT   550
 551  LLGDINISQPDLLKCTLKEYQVKGLNWLANLYEQGINGILADEMGLGKTV   600
 601  QSISVLAYLAETHNIWGPFLVVTPASTLHNWQQEISRFVPEFKVIPYWGN   650
 651  AKDRKVLRKFWDRKNFRYGKDAPFHVLVTSYQLVVADAAYFQKMKWQYMI   700
 701  LDEAQAIKSSQSSRWKSLLSFSCRNRLLLTGTPIQNSMQELWALLHFIMP   750
 751  SLFDSHDEFSDWFSKDIESHAQSNTELNEQQLRRLHVILKPFMLRRIKKN   800
 801  VQSELGDKLEIDVFCDLTHRQKKYYQMLTSQISIMDLLDSANNSSDDSAQ   850
 851  SLMNLVMQFRKVCNHPDLFERADVKSSFAFGRFAETSSFLRETNELEMSY   900
 901  STENLIKYNMPRIVYEEILQPTFDNDVGSRKKINNMFNIYHPSNIANDEL   950
 951  ENFSWLRFVDQSPQEMNNLSKQNIIERAINNREYSDINYERINRLKYTYD  1000
1001  EDNESFLPNSKLLLINELQNNHALISNSTYLKELYSIKKKVYEDMVINNM  1050
1051  KPAAEPLVKAPPVAVVCDNISFVHDLQDSLFDPKIRSSLMPLPFNRELEL  1100
1101  LKSSIPITEYPKSNMLPNAINKFIDYSNIRMPSMNRFITESGKLSKLDEL  1150
1151  LVDLRQNDHRVLIYFQMTKMMDLMEEYLTYRQHKYIRLDGSSKLDDRRDL  1200
1201  VHDWQTKPEIFVFLLSTRAGGLGINLTAADTVIFYDSDWNPTIDSQAMDR  1250
1251  AHRLGQTRQVTVYRLLTRGTIEERMRDRAKQKEQVQQVVMEGKSAIANKE  1300
1301  ESGNKKKDVAFLLLGNDDSSAAALNDDSEEKQNLQDSKKSQAKNLEDMYH  1350
1351  EGEGEFSGNVTPSL                                      1364

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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