Gene Wiki and Wikimedia Foundation SPARQL workshop
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Introduction to gene wiki project, the centralized model organism project and the use of SPARQL.
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Gene Wiki and Wikimedia Foundation SPARQL workshop
- 1. CURATING BIOMEDICAL KNOWLEDGE ON WIKIDATA AND WIKIPEDIA GENE WIKI Benjamin Good The Scripps Research Institute, La Jolla, California bgood@scripps.edu Twitter: @bgood
- 2. Gene Wikidata Team Andrew Su (Scripps) Andra Waagmeester (Micelio) Sebastian Burgstaller (Scripps) Tim Putman (Scripps) – speaking next Julia Turner (Scripps) Elvira Mitraka (U Maryland) Justin Leong (UBC) Lynn Schriml (U Maryland) Paul Pavlidis (UBC) Ginger Tsueng (Scripps) ACKNOWLEDGEMENTS
- 3. “knowledge” • A lot • Important • Text
- 4. More than 2 articles published/minute
- 5. Documents Concepts Gene Wiki: Filtering and summarizing PubMed
- 6. GENE WIKI 6 Protein structure Symbols and identifiers Tissue expression pattern Gene Ontology annotations Links to structured databases Gene summary Protein interactions Linked references Huss, PLoS Biol, 2008 Bot!
- 8. Gene Wiki Version 1. {{GNF_Protein_box | Name = Reelin| image = | image_source = | PDB = {{PDB2|4AD9}} | HGNCid = 18512 | MGIid = | Symbol = LACTB2 | AltSymbols =; CGI-83 | IUPHAR = | ChEMBL = | OMIM = None | ECnumber = | Homologene = 9349 | GeneAtlas_image1 = | GeneAtlas_image2 = | GeneAtlas_image3 = | Protein_domain_image = | Function = {{GNF_GO|id=GO:0005515 |text = protein binding}} {{GNF_GO|id=GO:0016787 |text = hydrolase activity}} {{GNF_GO|id=GO:0046872 |text = metal ion binding}} | Component = {{GNF_GO|id=GO:0005739 |text = mitochondrion}} | Process = {{GNF_GO|id=GO:0008152 |text = metabolic process}} | Hs_EntrezGene = 51110 | Hs_Ensembl = ENSG00000147592 | Hs_RefseqmRNA = NM_016027 | Hs_RefseqProtein = NP_057111 | Hs_GenLoc_db = hg38 | Hs_GenLoc_chr = 8 | Hs_GenLoc_start = 70635318 | Hs_GenLoc_end = 70669174 | Hs_Uniprot = Q53H82 | Mm_EntrezGene = 212442 | Mm_Ensembl = ENSMUSG00000025937 | Mm_RefseqmRNA = NM_145381 | Mm_RefseqProtein = NP_663356 | Mm_GenLoc_db = mm10 | Mm_GenLoc_chr = 1 | Mm_GenLoc_start = 13623330 | Mm_GenLoc_end = 13660546 | Mm_Uniprot = Q99KR3 | path = PBB/51110}} = Gene Wiki Version 2. {{Infobox gene}} • All data in Wikidata • 1 Lua script works for all 11,000+ genes = (1 of these for every gene) IMPACT OF WIKIDATA ON WIKIPEDIA
- 9. IMPACT BEYOND WIKIPEDIA = SPARQL
- 10. Sample of current biomedical content • All human, mouse genes and proteins • All Gene Ontology terms (describe function) • All Human Disease Ontology terms • All FDA approved drugs • 109+ reference microbial genomes Burgstaller-Muelbacher et al (2016) Database Mitraka et al (2015) Semantic Web Applications for the Life Sciences Putman et al (2016) Database
- 11. http://tinyurl.com/biowiki-sparql Sample queries that are currently possible: • “where in the cell is the Reelin protein expressed?” • “What diseases are treated by Metformin” • “What diseases might be treated by Metformin” http://query.wikidata.org
- 12. Example question: repurposing Metformin http://tinyurl.com/zem3oxz Metformin ?disease interacts with protein geneencoded by genetic association Might treat ? Solute carrier family 22 member 3 SLC22A3 prostate cancer
- 14. A SPARQL powered user interface for consuming and editing organism data in Wikidata Timothy E. Putman Ph.D. The Scripps Research Institute, La Jolla, California tputman@scripps.edu Twitter: @putmantime
- 15. Gene Wikidata Team Andrew Su (Scripps) Benjamin Good – just spoke Andra Waagmeester (Micelio) Sebastian Burgstaller (Scripps) Elvira Mitraka (U Maryland) Julia Turner (Scripps) Justin Leong (UBC) Lynn Schriml (U Maryland) Paul Pavlidis (UBC) Ginger Tsueng (Scripps) ACKNOWLEDGEMENTS
- 16. Centralizing and Linking the Data Bacteria Q10876 domain TRPA Q21153984 protein C.trachomatis Q131065 species trpA Q21153861 gene C. trachomatis 434/BU Q20800254 strain
- 22. SPARQL Query • On page load • JQuery execution of SPARQL query as AJAX GET Request
- 24. • On organism select • Get all gene and protein data for organism by taxid
- 34. QUESTIONS?
Editor's Notes
- Knowledge is either not shared (stuck in your head or your notebook) or it is shared as text and images in journal articles. There are more than 1 million articles added to PubMed each year
- Relying on the entire community of scientists to digest the biomedical literature: identification filtering extraction summarization
- Now we can use a database instead of wikitext to store data. great! and opens up other possibilities
- Using this linked data model . For a bacterial genome, each genetic item is linked to the taxonomic hierarchy, and the gene and protein are distinct entities. The gene having genomic annotations, the protein functional annotations, and them both being linked by the encodes and encoded by properties.
- So here is the wikidata item that represents the strain or subspecies taxa in our data model. Now we can navigate through the graph by following the statements that lead to other wikidata items. So for example if you click on parent taxon, you go to the species level item …
- chlamydia trachomatis,if you kept going in that direction, once you have gone through genus, family, order etc.. you would eventually reach bacteria King Phillip Came Over From Great Spain.
- IF you go in the other direction, you get to the genes found in that taxon through the predicate of that name, that gene is linked to its product through encodes
- and its product is linked back to its gene through encoded by, and the strain also through found in taxon. On the protein is where you would find functional annotations such as GO terms.