Identifying aberrant pathways through integrated analysis of knowledge in pharmacogenomics

Many complex diseases are the result of abnormal pathway functions instead of single abnormalities. Disease diagnosis and intervention strategies must target these pathways while minimizing the interference with normal physiological processes. Large-scale identification of disease pathways and chemicals that may be used to perturb them requires the integration of information about drugs, genes, diseases and pathways. This information is currently distributed over several pharmacogenomics databases. An integrated analysis of the information in these databases can reveal disease pathways and facilitate novel biomedical analyses.

Results: We demonstrate how to integrate pharmacogenomics databases through integration of the biomedical ontologies that are used as meta-data in these databases. The additional background knowledge in these ontologies can then be used to enable novel analyses. We identify disease pathways using a novel multi-ontology enrichment analysis over the Human Disease Ontology, and we identify significant associations between chemicals and pathways using an enrichment analysis over a chemical ontology. The drug–pathway and disease–pathway associations are a valuable resource for research in disease and drug mechanisms and can be used to improve computational drug repurposing.

Availability: http://pharmgkb-owl.googlecode.com

Don't Hog the Data | The Daily Scan | GenomeWeb

The UK Royal Society says that for science to work, it has to be as open as possible, reports Richard Van Noorden at the Nature News blog. In a new report, the society says that researchers who hog their data are presenting a "serious impediment" to scientific process, adding that "science is an open enterprise." Furthermore, the report adds, it's not enough for researchers to allow access to their data. What's needed is the kind of openness where researchers talk to each other about data, especially when speaking to researcherswho are specialists in other fields who might be able to use that data in their own work, Van Noorden says. "Many scientists already appreciate the value of sharing data sets in organized public databases, simply because it provides more efficient and creative ways to do research," he adds. "But some still cling possessively to their data, and top-down constraints, such as the lack of recognition for generating and communicating data, also blunt the urge to share." The report adds that researchers have to learn to adjust to the large volumes of data that are common today, and invest in good data management tools and training.