Allison Heath: CS and Genomics

Rice CS alumna Allison Heath.

Allison Heath arrived at Rice University as a Physics major. “Then I took COMP 210 with Keith Cooper,” said the Rice alumna (B.S. ‘04, M.S. ‘07, Ph.D. ‘10).

“Keith’s teaching inspired me to pursue what I had previously considered only a hobby. So, I took more computer science classes and ended up changing my major.”

In her second semester, she took a class taught by Lydia Kavraki, who suggested Heath consider research opportunities in her lab. Heath said she spent almost every summer of her undergraduate years working in the Kavraki lab.

“Bioinformatics was exciting and new, even though I thought it was a silly sounding word when I first heard it. But collecting and analyzing streams of biological data fit perfectly with my interests in physics and related algorithms.”

Heath structured her degree plan to include both undergraduate and graduate level CS coursework. Taking two semesters of biochemistry and cell biology was also a wise investment of her time. She said some computer scientists working in bioinformatics learn what they need to know about biology on the fly, but an opportunity to focus on the topics as a student laid a strong foundation that she continues to appreciate.

“I wish more people in the field could cross-train in those disciplines –biological researchers learning algorithms and programming, and computer scientists understanding biology and biochemistry. Rice gave me that flexibility, plus the opportunity to work on collaborative projects blending my training in CS with biology in the Kavraki Lab.

“For my master’s, I had the chance to work with Cecilia Clementi in the Department of Chemistry on protein structures, then with Gábor Balázsi at MD Anderson on gene networks. My Ph.D. research with George Bennett in the Department of Biochemistry helped develop new algorithms for use in genome-scale metabolic networks.”

After completing her Ph.D. at Rice, Heath worked in the technology industry for a year. Then genomics slid onto her radar, causing her to return to academic research at the University of Chicago.

Heath said, “As part of the NCI Genomic Data Commons, we were aggregating, harmonizing and distributing petabyte-scale data. How could we create a system flexible enough to accommodate complex work flows and robust enough to distribute data to the world?

Data had to flow effectively, which meant we needed to think about data structures and protocols. Beyond the technology challenges, we had to knit together a team with the breadth of expertise required to serve the needs of the global cancer community.”

Her work at the University of Chicago revealed the strength of her overlapping understanding of both CS and biology. Biomedical research that grows increasingly data-driven and data-informed is driving the demand for computer scientists who can imagine and build technology systems and solutions to meet the requirements of the medical community.

With her move to the Children’s Hospital of Philadelphia, Heath is now working at the intersection of translational research and clinical care on behalf of pediatrics in the Center for Data-Driven Discovery in Biomedicine (D3b). One of her major projects is the Gabriella Miller Kids First Data Resource Center which supports collaborative analysis of large-scale clinical and genomic data to accelerate discovery and understanding of structural birth defects and pediatric cancers.

“We are already getting genomic sequences from people as part of their patient care,” said Heath. “What if we can link medical records to clinical outcomes and disease registries, to better understand both clinical and genomic data? How can we leverage that data to translational research, develop new therapies, and bring that wealth of information into day-to-day patient care?”

The abundance of data and myriad therapies complicates the integration of the different streams of information, and professionals on both sides of the data have to learn how to communicate their needs.

Heath said, “The research involves multiple people with expertise in different specialties, speaking different languages. Often times, the key people in the process are the ones who can talk to both sides in their own languages. Facilitating the flow of data and knowledge impacts the entire cycle, and we know there is a gap in how things get done if we don’t have the translators.”

At Rice, there had been a different type of gap in her experience. Although some of her undergraduate friends created CSters, a club supporting women in CS, Heath said she had not noticed how few women there were among her peers until she won an award.

“I was being interviewed about winning an NSF Graduate Fellowship when the reporter asked me how it felt to be a woman in computer science. I had never considered it. It was like asking me how it felt to have arms.

“That was an important touchstone and I wondered why I had never recognized the gender imbalance. I didn’t go to Grace Hopper Celebration until 2006, and it was revolutionary. It made me realize how different the tech world could look.”

Heath said now that she has the chance to form her own teams, she strives for diversity across gender, culture, and fields of study.

“Our teams have biologists, engineers, physicists, computer scientists, MDs, PhDs, and people who went straight into industry from high school, from all around the US and the world” she said.

“Diversity is critical for solving the hardest problems in this world. A homogeneous group of people won’t be as powerful as a team of people that bring various backgrounds and context to the table. People with different perspectives often reframe the question. Sometimes, simply asking the same old questions in new and different ways can reveal the solution.”