With our relatively newfound ability to perform large-scale surveys of the genomic and proteomic landscape, the principal challenge has shifted away from measurement toward interpretation of the data.
Our group has been developing and using analytical approaches rooted in information theory and formal dynamic systems theory to infer biological structure and function in these large data sets. More recently we have integrated data-driven techniques with natural language processing to more formally draw upon the research community’s collective knowledge.
In particular, we have been integrating these approaches to decipher the principles of operation of the immune system by mapping its internal communication network as well as its participation in neuro-endocrine signaling.
Our eventual goal is not only to tap into pathogenic immune conversations but also more importantly to re-direct these conversations with a limited number of well-chosen and well-timed pharmaceutical messages. This research is founded on the premise that for immune therapies to be both safe and effective the immune system must be considered as an integrated whole.
Elsevier Connect "How text mining is changing the way we tackle chronic disease", November 2017
Science Magazine, July 2017