Course Goals

  • Understand the theoretical concepts behind gene co-expression and gene regulatory networks.
  • Understand how to apply several existing gene co-expression and gene regulatory methods.

In order to capture nonlinear relationships and complex interactions, network analyses are applied in many different biological contexts. This module will provide hands-on experience in the analysis of two specific types of biological networks—gene co-expression networks and gene regulatory networks. During the module, faculty will review the scientific theory involved in these methods and then participants will apply the theory to real data sets. After completing the module, participants should to be able to apply these methods in their own research.

Session dates

Harvard Catalyst in-person learning is suspended due to COVID-19 precautions. Please refer to Online Learning for current offerings.

Time commitment

One day


MD, DNP, PhD or equivalent, DDS/DMD.

We believe that the research community is strengthened by understanding how a number of factors including gender identity, sexual orientation, race and ethnicity, socioeconomic status, culture, religion, national origin, language, disability, and age shape the environment in which we live and work, affect each of our personal identities, and impacts all areas of human health.


  • R programming experience
  • Past participation in Harvard Catalyst’s Introduction to Network Medicine course, or willingness to watch selected recorded lectures from the three-day course prior to this course


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Accreditation statement

Harvard Catalyst Postgraduate Education Program’s policy requires full attendance and the completion of all activity surveys to be eligible for CME credit; no partial credit is allowed.

The Harvard Catalyst Education Program is accredited by the Massachusetts Medical Society to provide continuing medical education for physicians.


The application process is closed. Please check back for future opportunities.