Contact:

Aaron Cohen, M.D.
Oregon Health and Sciences
University,
Dept of Biomedical Informatics
cohenaa@ohsu.edu

For our Pharma Partners:

Use Foci-of-Expertise to find an expert in the disease or target

Use the Foci-of-Expertise to identify a researcher or a cluster of researchers that study your target of interest in a context of a new disease.

By knowing the target of your drug, FoX helps you to identify the researchers associated with that particular target.

Then the names of researchers are linked to the disease they are interested in. Potentially, several associated researchers may have different ideas, models, tools to study the same target, and could potentially form a multisite team to provide a proof of concept for a new drug indication.

cloud filtered

Foci of Expertise

Foci of Expertise (FoX) is  a tool that allows exploration of targets and diseases and their associated expertise among the CTSA researchers.

1. Most of the drugs have known targets
2. The data on protein or gene target is in the foundation of the FoX
3. Researchers are linked to the target based on their publications
4. Researchers are also linked to diseases based on their publications
5. Overlap between a target and a disease provides a starting point for finding the expert in the field for drug repositioning
6. The networks originated from this linkage are visualized by Synergy, a tool developed by OHSU.

foci of expertise

For the pilot project, we obtained the first tranche of data from Biovista (www.biovista.com), covering 5 CTSA institutions. The data provided us with critical linkages between researcher-target and researcher-disease. We completed relationships between gene/protein and disease by mining OMIM and other databases.

Additionally, we linked the target proteins into biologically significant pathways by mining the KEGG, IntACT, Reactome, and HPRD databases, resulting in protein-protein linkages.

This is an example of data cloud with interacting protein targets (in
blue), associated researchers (in red) and linked diseases (in green)

 

cloud

 

We will be designing various filters to make this data to ensure usability. Examples of filters include: filter by the name of the institution, by data of publication , by frequency of publications etc.