BioSymphony
Orchestrating tomorrow's biomedical research collaborations



INTRODUCTION

Solving complex biomedical problems relies more and more on collaborative efforts among two or more investigators each with different skills and expertise.  It is often the case that the most useful collaborations result from chance interactions among investigators from different departments at the same institution or among
investigators at different institutions from the same region.

OBJECTIVE

The goal of the BioSymphony project is to develop and make freely available software for facilitating biomedical research collaborations. We are establishing a database of biomedical investigators at Dartmouth and throughout Northern New England that consists of annotated information about each investigator mined from PubMed that can be used to predict fruitful collaborations.  Our hope is that this resource will result in meaningful collaborations that otherwise might happen only by chance.

SOFTWARE

The BioSymphony (BioSym) database and software is in early alpha testing at Dartmouth Medical School.  Sometime in early 2007 we plan to make available a prototype web interface to the database that will allow investigators to visually explore networks of predicted collaborations.  Check this web page or our blog (Epistasis Blog) for updates.

EXAMPLE

The following interaction graph illustrates both inter- and intra-center relationships predicted from the number of Medical Subject Heading (MeSH) terms extracted from published papers in PubMed that each pair of investigators shares.  Shown are project PIs from the COBRE-funded Lung Biology Center (Duell, Madden, O'Toole, Swiatecka-Urban, and Treadwell) and the COBRE-funded Center for Molecular, Cellular, and Translational Immunological Research (Berwin, Conejo-Garcia, Kelly, Ernst) at Dartmouth College.  The number in each box is the total number of unique MeSH terms that each investigator has.  The number next to a line connecting two investigators is the number of MeSH terms those two people share in common.  We have highlighted in red connections with more than five shared MeSH terms.  Investigators not shown in the graph (Kelly and Ernst) had no MeSH terms in common with anyone else.  The important observation from this graph is that two of the three strongest connections are among investigators from different centers.  These inter-center relationships could be predictive of potential fruitful collaborations among investigators with otherwise disparate interests and expertise.




This page was last updated Januray 29, 2007 by JHM