Bridging biology and computer science

The languages of computer science and biology can seem worlds apart, but translators like Asst. Prof. Samantha Riesenfeld are here to bridge the fields—and show just how much insight speaking two languages can reveal.

An expert in computational biology, Riesenfeld develops and uses machine learning methods to investigate hidden processes driving biological systems. Much of her work involves analyzing large data sets to address fundamental questions about the immune system—including how different cells in a tissue interact to drive essential or pathological inflammation.

To do so, she and her team leverage genomic and transcriptomic data to model the behavior of cells, continuously translating between computationally detected signals and biological interpretations—both within the team and with their collaborators.

“Computer scientists call me a biologist, and biologists call me a computer scientist,” she said. “My lab has students from computer science, chemistry, physics, immunology, and engineering. Even though none of us speaks exactly the same language, we have stimulating discussions and really benefit from each other’s expertise. Many emerging fields are shaped by scientists who can bring together people and perspectives from different disciplines.”

Understanding different perspectives

In fact, Riesenfeld has played the role of translator most of her life. She speaks several human languages (including French and Italian, the native language of her husband, as well as understanding Spanish and some Hebrew) and programs in multiple languages. And though her parents—both professors of computer science—taught her math and programming at an early age, she was just as interested in creative pursuits like music and writing.

She ultimately pursued a PhD in theoretical computer science with the intent of staying firmly in that field. But an interdisciplinary project on evolutionary biology opened a door to a whole new world of research possibilities.

“I realized one of my favorite parts about research was meeting with scientists who have a totally different perspective,” she said.

Though she had no formal biology training, she delved into literature on molecular biology and genomics, and started a postdoc where she learned statistical techniques and worked closely with experimental biologists. “I began to appreciate how much the transcriptional machinery of cells is guided by control structures, and that reminded me of an engineered system,” she said. During a second postdoc, she joined an immunology-focused project, where she used new single-cell transcriptomic technologies to study a then-recently discovered type of immune cell.

Now, she and her team work on finding the signals in noisy, complex datasets—from both mouse models and patients—that can offer clues about the underpinnings and dynamics of the immune system.

“While we do experiments with specific questions in mind, we cannot anticipate the insights such rich data can reveal. So, we use our tools both to answer the questions we have in mind and to enable the data to tell us what questions we should be asking and what the answers might look like,” she said. The Pritzker School of Molecular Engineering has only helped her interdisciplinary work flourish, she says. “There is great energy and open-mindedness in PME around interdisciplinary approaches.”

Direct relevance to patients

Last year, she and collaborators modeled the response of innate lymphoid cells (ILCs), immune cells that reside in barrier tissues, to interleukin-23—a cytokine implicated in psoriasis. They found that ILCs change their behavior in unexpected ways to produce the downstream inflammatory signals that cause psoriatic lesions.

More recently, she and her team are creating and applying tools to understand how T cells, such as gamma-delta T cells, develop and become primed for specific immune responses, which drive inflammation in various tissues, including the intestine, skin, and brain. The ultimate goal is to learn how to better treat or even cure autoimmune and other inflammatory diseases.

“Understanding what causes these diseases—what helps maintain tolerance to an antigen, what causes a patient to lose tolerance to antigen, and what determines the features of an immune response—has direct relevance for human patients,” she said. “Our discoveries will help fuel the development of successful clinical interventions.”