Course offering an introductory overview of network science in biology and medicine. Introduction to Network Medicine
At a glance
Opportunity for
  • An introduction to the developing field of network science in biology and medicine.
Eligibility
  • MD, DNP, PhD or equivalent, DDS/DMD
  • Receipt of endorsement from an applicant's supervisor stating the applicant will be able to attend all days of the course.
Time commitment
  • Three days
Funding level
  • Tuition-free
Session dates
  • November 3-5, 2014
Application Due
  • 5:00pm on September 18, 2014
  • Applications and endorsements are due by this date
Notifications
  • All applicants will be notified of their status via email no later than September 26, 2014.
The application process is closed. Please revisit the webpage in spring 2015 for new opportunities.

This three-day course offers an introduction to a rapidly emerging field that integrates systems biology and network science. Network medicine runs counter to the prevailing scientific reductionist trend that dominates current medical research on disease etiology and treatment. Reductionism relies on single molecules or single genes to provide comprehensive and robust insights into the pathophysiology of complex diseases. Similarly, current drug development methodologies target single molecules that very frequently fail because of the unforeseen and unintended effects that result from the application of this piecemeal approach to pharmacology.

In contrast, network medicine emphasizes a more holistic approach through the identification and investigation of networks of interacting molecular and cellular components. When network medicine is integrated into biomedical research, it has the potential to transform investigations of disease etiology, diagnosis, and treatment.

This course will explore the network medicine concept through (1) a review of the role, identification, and behavior of networks in biology and disease, (2) the integration of multiple types of -omics data into perturbed, dynamic networks as a paradigm for understanding disease expression and course, and (3) systems pharmacology approaches for the development and evaluation of effective therapies of complex disease.