Kimberly Glass-profileKimberly Glass, PhD
John Quackenbush-profileJohn Quackenbush, PhD

Citizen Scientist Summaries_Hypothesis 1 (PDF)

Abstract-Kimberly_Glass and John_Quackenbush (PDF)

CV Kimberly Glass (PDF)

CV John Quackenbush (PDF)

Presentation Kimberly Glass and John Quackenbush (PDF)

Kimberly Glass, PhD, Postdoctoral Fellow in the Department of Biostatistics and Computational Biology at Dana-Farber Cancer Institute and Harvard School of Public Health

Kimberly Glass obtained her PhD in Physics from the University of Maryland in College Park in 2010. Her thesis research there focused on the mathematical theories behind complex network structure. While in Maryland she also simultaneously obtained training in biological science and analysis of genomic data through collaboration with bench biologists at the National Cancer Institute in Bethesda, Maryland. After graduation, Kimberly became a postdoctoral fellow at Dana-Farber Cancer Institute and the Harvard School of Public Health. Since joining, her main research focus has been on developing computational approaches to better understand the basic principles underlying organism development and diseases. In particular, she has recently developed a computational method to infer genome-wide regulatory networks.

John Quackenbush, PhD, Professor of Biostatistics and Computational Biology and Professor of Cancer Biology,
Dana-Farber Cancer Institute, Director, Center for Cancer Computational Biology, Dana-Farber Cancer Institute, Professor of Computational Biology and Bioinformatics, Harvard School of Public Health

John Quackenbush received his PhD in 1990 in theoretical physics from UCLA working on string theory models. Following two years as a postdoctoral fellow in physics, Dr. Quackenbush applied for and received a Special Emphasis Research Career Award from the National Center for Human Genome Research to work on the Human Genome Project. He spent two years at the Salk Institute and two years at Stanford University working at the interface of genomics and computational biology. In 1997 he joined the faculty of The Institute for Genomic Research (TIGR) where his focus began to shift to understanding what was encoded within the human genome. Since joining the faculties of the Dana-Farber Cancer Institute and the Harvard School of Public Health in 2005, his work has focused on the use of genomic data to reconstruct the networks of genes that drive the development of diseases such as cancer and emphysema.

Kimberly & John

Together with Dr. Guo-Cheng Yuan, we began a project a few years ago to model the flow of information through transcriptional networks. After hearing about our work, Dr. Curtis Huttenhower suggested that what we were doing was similar to a method called “affinity propagation” or “message passing” that had developed in communication theory. As we refined the approach and its application, we developed PANDA (Passing Attributes between Networks for Data Assimilation). PANDA recognizes that information flow requires the involvement of both a transmitter and a receiver and uses that concept to integrate multiple types of data by searching for the transcriptional network most consistent with the biological context. We’ve used PANDA to investigate a wide range of problems, including a project suggested by Dr. Dawn DeMeo exploring sexual dimorphism in the development and progression of chronic obstructive pulmonary disease. When we learned about the Alzheimer’s challenge, we realized that this was the perfect question to explore using PANDA. We were very excited to see such clear differences in the gene regulatory networks in male and female brains and to observe how those networks are rewired as Alzheimer’s develops. What was even more exciting to us was the intuitive nature of the differences we observed driven, in part, by genes known to be responsive to estrogen and testosterone.

Kimberly’s mother formally worked as a nursing home activities director, during which time she oversaw the special Alzheimer’s unit. Her shared stories have created a personal connection for Kimberly with people affected by Alzheimer’s. John’s grandmother died from Alzheimer’s disease.