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Swan River foreshore, Perth, Western Australia University of Western Australia Biomedical, Biomolecular and Chemical Sciences.

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Presentation on theme: "Swan River foreshore, Perth, Western Australia University of Western Australia Biomedical, Biomolecular and Chemical Sciences."— Presentation transcript:

1 Swan River foreshore, Perth, Western Australia University of Western Australia Biomedical, Biomolecular and Chemical Sciences

2 Ian SmallMurray BadgerDavid DayHarvey Millar Steve SmithBarry PogsonJim Whelan ARC Centre Plant Energy Biology

3 SUBA SUBcellular location database for Arabidopsis proteins Sandra Tanz and Ian Castleden 4 th March 2011

4 Why protein localisation? Contributes towards the understanding of protein function and of biological inter-relationships, i.e. only proteins in the same location can interact. Separate subcellular locations often represent distinct cellular environments: proteins share similar attributes and play roles in defining the function of a subcellular compartment. To build hypotheses or models: large-scale phenotyping screens, microarray experiments and protein-protein interaction assays rely on protein localisation info.

5 How to localise proteins? Prediction In vitro uptake (imports) In vivo (GFP) Enzyme activity measurements Western blot Immunogold labeling Subcellular proteomics (MS) Protein-protein interaction Images modified from Millar et al., 2009

6 SUBA: SUBcellular location database for Arabidopsis proteins

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8 What does SUBA document? MS (6398)GFP (2135) SUBA II (2007)SUBA III (2011) Combined sub-location data 250’719 1’022’040 Calls by PPI Calls by experiments (GFP, MS)827319’528 Distinct proteins localised by GFP and/or MS Bioinformatic predictions by10 predictors24 predictors NEW!

9 Data mining Search of the NCBI PubMed (Medline) and Entrez (GenBank) databases using keywords Alert via

10 Data mining Search publication to extract localisation information = fully curated data

11 SUBA III interface

12 SUBA III interface

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25 SUBA III flatfile

26 Analysis of SUBA III data – on the way… Do data become more or less consistent over time? Experimental data (MS vs GFP) How reliable are experimental localisation data? Has the overlap of data changed with increasing data sets?

27 How reliable are GFP localisation data? Total GFP localisations confirmed by MS Total GFP localisations disputed by MS MS (9016)GFP (2554) MS (74172)GFP (1844) 1386 neither confirmed or disputed

28 Analysis of SUBA III data – on the way… Do data become more or less consistent over time? Experimental data (MS vs GFP) How reliable are experimental localisation data? Has the overlap of data changed with increasing data sets? Does evidence for multiple locations mean the protein is dual targeted/dynamic or is it a false positive? Prediction vs experimental data How reliable are predictors today? PPI data What do PPI data tell us about sub-cellular location? Organellar proteome: Can we discover novel organellar proteins?

29 SUBA under the hood

30 Why a Web interface? GeneInvestigator, MapmanGeneInvestigator AHM chemicals (Apache JPA)AHM chemicals For the foreseeable future databases are going to be “Web” based (HTTP, Javascript, HTML,css) Need to be maintained by a minimum number of developers (i.e. one!)

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32 SUBA Tables (predictors)

33 SUBA Tables (“original” sources)

34 Suba Tables (publications) etmode=xml&id=

35 SUBA Tables (automation)

36 Julian Tonti-Filippini

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38 Why Bother?

39 SELECT suba3.suba3.*, suba3.src_ppi_1.* FROM suba3.suba3 LEFT OUTER JOIN suba3.src_ppi AS src_ppi_1 ON suba3.suba3.locus = src_ppi_1.`locusA` WHERE EXISTS (SELECT 1 FROM suba3.src_ppi WHERE suba3.suba3.locus = suba3.src_ppi.`locusA` AND suba3.src_ppi.`locusB` IN (‘AT3G ’)) “denormalisation” src_msms Suba2

40 Suzanne M. Embury and Peter M.D. Gray

41 Computational Systems Biology Centre of def query(filter,offset=0,limit=1000): return Session().query(Suba3).filter(json2sqla(filter))\.offset(offset).limit(limit) t','gt', ]&offset=0&limit=1000 {success: True, result:[ { locus:’AT1G ’, mwt:81454, …. ppi:[{locusA:’AT1G ’,locusB:’AT1G ’,pubmed: }] }, { locus:’AT1G ’, mwt:91454, …. ppi:[{locusA:’ AT1G ’,locusB:’AT1G ’,pubmed: }] }, … ] }

42 Computational Systems Biology Centre of Excellence (Near) Future Large number of predictors often given conflicting predictions… what to do? Bayesian analysis…

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44 Acknowledgements Ian Small Harvey Millar Joshua Heazlewood Julian Tonti-Fillipini Thanks for your attention!!


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