BioRDF Update

Kei Cheung, Ph.D.Yale Center for Medical Informatics

CSHALS 2010: HCLS Tutorial, Boston, February 23, 2010

Current participants• Kei Cheung (Yale University) • Helena Deus (University of Texas) • Don Doherty (Brainstage) • Rob Frost (Vector C) • 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)

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

Query federation in the context of neuroscience microarray data

Gene expression in the neurosciences• 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

Microarray examples/use cases

• NIH Neuroscience Microarray Consortium and EBI ArrayExpress

• RDF representation of experiment metadata and gene lists including provenance

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• Disease state• Treatment

Approach

• Reuse existing ontological terms and relationships (e.g., OBO Relation Ontology)

• Use Provenir ontology and aTags• Create RDF representation of gene lists

RDF representation of gene expression listsGenelist 1

Genelist 2

Genelist 3

Gene-specific annotationSample-specific gene expression valuesAggregated gene expression values

RDF graph

gene1

name

symbol

probeid

sample1

Expression_value_for_gene1_sample1_pair

value

context

503.7

“Signal”

Expression_value_for_gene1_sample1_pair

value

context

“P”

“Detection”

Brain_region

“Entorhinal Cortex”

“AD”Disease_status

“225871_at”

“STEAP2”

“six transmembrane epithelial antigen of prostate 2”

Organism“Human”

Live to 100!

Ginkgo, the oldest surviving species of tree, has been traced back 300 million yearsand 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; ginkgohas 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 longevitytonic 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.

Featured Blog (from Ask Dr. Mao)

Feeling like the absent-minded professor lately?

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

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• Demos (e.g., iPhone application)• Expand the TCM project

The End