1 / 15

BioRDF Update

BioRDF Update. Kei Cheung, Ph.D. Yale Center for Medical Informatics. CSHALS 2010: HCLS Tutorial, Boston, February 23, 2010. Keyword-based query vs. Knowledge-based query (Syntactic Web vs. Semantic Web). I’m NOT a company!. Kei (Hui) Cheung Not me!. Kei (Hoi) Cheung (15 years ago).

jesusn
Download Presentation

BioRDF Update

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. BioRDF Update Kei Cheung, Ph.D. Yale Center for Medical Informatics CSHALS 2010: HCLS Tutorial, Boston, February 23, 2010

  2. Keyword-based query vs. Knowledge-based query(Syntactic Web vs. Semantic Web) I’m NOT a company! Kei (Hui) Cheung Not me! Kei (Hoi) Cheung (15 years ago) Kei (Hoi) Cheung (more recent) Find the most recent image of the person “Kei Hoi Cheung”

  3. Current BioRDF participants Kei Cheung (Yale University) Helena Deus (University of Texas) Don Doherty (Brainstage) Rob Frost (Vector C) M. Scott Marshall (University of Amsterdam) Michael Miller (Teranode) Adrian Paschke (Freie Universitat Berlin) Eric Prud'hommeaux (W3C) Satya Sahoo (Wright State University) Matthias Samwald (DERI and Konrad Lorenz Institute) Jun Zhao (Oxford University)

  4. Current tasks Query Federation Semantic integration of neuroscience microarray data and related data Expansion of previous query federation work (Cheung et al. A journey to semantic web query federation in the life sciences. BMC Bioinformatics. 10(Suppl 10):S10, 2009) Traditional Chinese Medicine (TCM) Collaboration with LODD Linking TCM data and other types of data including drug data

  5. Query federation in the context of neuroscience microarray data

  6. Microarray Gene expression in neuroscience Gene expression may be an indicator of how well someone is aging The New England Centenarian Study DNA microarray technology allows scientists to scan tens of thousands of genes from a single sample at a time and then link them to specific biological functions

  7. Microarray examples/use cases NIH Neuroscience Microarray Consortium and EBI ArrayExpress RDF representation of experiment metadata and gene lists including provenance Inter-community collaboration: semantic web, ontology, neuroscience, microarray communities.

  8. Representative concepts Disease (e.g., AD, PD) Neuron (e.g., dopamine neuron) Brain region (e.g., hippocampus, posterior cingulate cortex, visual cortex) Brain function (e.g., unimodal and heteromodal sensory association) Organism (e.g., human) Experimental factor (e.g., normal vs. AD) Sample extraction method (e.g., laser-capture microdissection) Proteins (e.g., NFT) Genes (e.g., gene lists) Biological process (e.g., energy metabolism) Cellular component (e.g., mitochondrial electron transport chain) Age (e.g., old) Disease state (e.g., mild vs. severe)

  9. Approach Reuse existing ontological terms and relationships (e.g., NIFSTD and OBO RO) Start using Provenir ontology and aTags Create RDF representation of gene lists

  10. RDF representation of gene expression lists Genelist 1 Genelist 2 Genelist 3 Gene-specific annotation Sample-specific gene expression values Aggregated gene expression values

  11. RDF graph probeid “225871_at” “Entorhinal Cortex” gene1 symbol Brain_region “STEAP2” sample1 “AD” Disease_status name “six transmembrane epithelial antigen of prostate 2” Organism “Human” 503.7 value Expression_value_for_gene1_sample1_pair context “Signal” value “P” Expression_value_for_gene1_sample1_pair context “Detection”

  12. Live to 100! Featured Blog (from Ask Dr. Mao)Feeling like the absent-minded professor lately? Ginkgo, the oldest surviving species of tree, has been traced back 300 million years and is one of the most widely studied plants. The leaf of the ginkgo tree is shaped like a human brain, and some believe this is why, in Asia, it has always had a reputation of benefiting the mental processes. A dwindling memory and decreased concentration is largely caused by decreased blood flow to the brain and loss of brain cells; ginkgo has been confirmed to boost circulation to the brain and other organs, improving memory and cognitive functions. Additionally, ginkgo is used far and wide as a longevity tonic in Asia and Europe. The best-known and most commonly available form of ginkgo is as teas and herbal extracts, but ginkgo nut, used in the culinary traditions of Asian cultures, also has therapeutic properties and is also said to strengthen lung function.

  13. TCM project milestone Collaboration between BioRDF and LODD A paper was recently submitted to BMC Chinese Medicine (Thematic Series: Semantic Web for Chinese Medicine) Samwald et al. Integrating findings from traditional medicine into modern pharmaceutical research through semantic technologies Linking a variety of data involving herbs that have been studied in terms of their potential therapeutic effects on depression Data sources: TCMGeneDIT, PubMed, DBPedia, PharmGKB Semantic Web technologies: aTag (including an aTAG explorer), RDFa, and SPARQL endpoint

  14. Future plan Federate microarray data with other types of data including data stored in HCLS KB’s (e.g., pathway data and disease/phenotype data) Explore a range of federated queries Provide use cases for shared names and RDB-RDF mapping Demos (e.g., iPhone application) Expand the TCM project

  15. Acknowledgement HCLS group Susie Stephens M. Scott Marshall Eric Prud’hommeaux NIH support SenseLab (P01 DC04732) Neuroscience Microarray Consortium (U24 NS051869)

More Related