Join us for our COMBINE Annual Symposium on
Network Biology

Friday May 13th, 2022
11:30am – 2:30pm
Kay Boardroom (Rm 1111), Kim Building
RSVP here

COMBINE (Computation and Mathematics for Biological Networks) is an NSF Research Traineeship (NRT) program at the University of Maryland, College Park (UMD). The program utilizes a network-based, data-driven approach, focusing on how interaction patterns can give insights into complex biological phenomena. 

The 2022 COMBINE Annual Symposium includes an interdisciplinary career panel, a poster session showcasing the work of graduate fellows, and a keynote talk on network biology. This event is an opportunity to learn more about network biology research at UMD and elsewhere, and connect with researchers across various disciplines.

Schedule:

11:30am – 11:35am	Introduction Prof. Michelle Girvan, COMBINE Director
11:35am -12:30pm	Panel – Navigating Interdisciplinary Career Paths Prof. Elizabeth Quinlan, Prof. Behtash Babadi, Prof. Wolfgang Losert Moderators: Joshua Lucker and Spandan Pathak (COMBINE Fellows)
12:30pm – 12:45pm	Poster previews by COMBINE Fellows
12:45pm – 1:30pm	Poster session and Lunch
1:30pm – 2:30pm	Keynote talk – Why Networks Matter JQ Abstract Prof. John Quackenbush, Harvard University

Keynote Presentation

Why Networks Matter: Embracing Biological Complexity

John Quackenbush

Harvard TH Chan School of Public Health, Channing Division of Network Medicine of Brigham and Women’s Hospital, and Dana-Farber Cancer Institute

One of the central tenets of biology is that our genetics—our genotype—influences the physical characteristics we manifest—our phenotype. But with more than 25,000 human genes and more than 6,000,000 common genetic variants mapped in our genome, finding associations between our genotype and phenotype is an ongoing challenge. Indeed, genome-wide association studies have found thousands of small effect size genetic variants that are associated with phenotypic traits and disease. The simplest explanation is that genes and genetic variants work together in complex regulatory networks that help define phenotypes and mediate phenotypic transitions. We have found that the networks, and their structure, provide unique insight into how genetic elements interact with each other and the structure of the network has predictive power for identifying critical processes in health and disease and for identifying potential therapeutic targets. I will touch on multiple examples illustrating the importance of network models, drawing on my work in cancer, in chronic obstructive pulmonary disease, and in the analysis of data from thirty-eight tissues provided by the Genotype-Tissue Expression (GTEx) project. We will use these to explore the development and progression of disease and new ways to identify therapeutics.