Biological Data

The Science of Biological Data

Fred Adler

In an age when cross-disciplinary collaboration has become a buzzterm, especially in academia, Fred Adler puts his mathematical models where his mouth is. Multi-disciplinary work—in which academic silos are breached in the search for truth—is the hallmark of what Adler, who has a joint appointment in mathematics and biology, does.

His is the kind of work that will be supported by the new science building recently announced by the College of Science, dedicated to applied and multi-disciplinary work, and where most STEM students at the U will eventually find themselves for a time.

As Director of the Center for Quantitative Biology, Adler and his team have applied their data-driven tool kit to everything from viruses to animal behavior, and from biodiversity to infectious diseases. Who else can claim a lab’s subject models as varied as aphid-tending ants, hantavirus, and the Southern Right Whale off the coast of Argentina?

Math in Nature

The Adler group’s approach to research is driven by basic questions about how biology works. To bring together several threads of research, the lab began a study of rhinoviruses, the most common cause of the common cold, and how they routinely and rapidly change. The study uses mathematical models based on known interactions in the immune system and genetic sequences. “We hope to build detailed evolutionary models of this rapidly change set of viruses,” Adler reports.

He and his team are now looking at cancer in humans. There are, of course, hypotheses of how cancer takes over cells in the body and grows. But too many of these hypotheses are based on assumptions that cells behave as they do with complete information and clever plans for the future instead of the confusing world of a real tissue.

“However useful some of these [current] models are,” says Adler, “they are not based on a realistic assumption.” In fact, a prime contribution of the mathematical modeler is “to make sense of things from the perspective of what you’re modeling.” What access to information does the cell or organism have, is a central, guiding question.

Muskan Walia and Emerson Arehart

Part of how cancer behaviors may be better scientifically “unpacked” is through game theory but expanded over time and space and placed in a context of incomplete information between constituent parts.

Mathematical models, or more accurately, an ensemble of models later aggregated like political polls or weather models to predict the future, may be the answer. “We usually don’t get a simple smoking gun,” says Adler referring to complicated questions in biology, whether developmental, behavioral-ecological, immuno- or micro-biological. “With nine or ten big mathematical models running all the time you have a [more robust] hypothesis,” he says.

“All thinking is done using modeling,” Adler reminds us, “whether it’s through language or, in my case, mathematics.” The strength of the latter is that when mathematical modeling is added to the classical biologist’s models, it is “perfectly explicit about its assumptions. When you do the math right (and we always do), the logic leading from assumptions to conclusions is airtight ‘true.’”

This is important because a mathematical argument can’t be controverted. “If conclusions in biological research are wrong, it’s the assumptions that are wrong,” and the researcher can then pivot on those assumptions.

Modeling of this kind, of course, has proven helpful, most recently, in the study of Sars-CoV-19, the virus that has propelled the world into a pandemic. The coronavirus does not operate in isolation, but with other components through the human immune system.

This kind of work is animated not just by its predictive character using statistics—as in the case of artificial intelligence or machine learning (“We aren’t all cyborgs, yet,” Adler says)—but, it is predictive in a mechanistic sense in that it cares deeply about the more nuanced and open-ended “how,” the foundation of the scientific method.

Adler started out at Harvard as a pure mathematician, but by the time he arrived at Cornell University as a graduate student, he had discovered that he really enjoyed talking and collaborating with biologists. Stanford-based Deborah Gordon, a renowned expert on ants, which as he puts it, “achieve a lot of stuff fairly robustly through simple rules,” was one of them. He also found himself with David Winkler in upstate New York in a bird blind and observing the breeding and offspring-raising behaviors of tree swallows. The complicated models he built based on that research were never published, but Adler was hooked on life sciences.

Whether it’s modeling the lungs of cystic fibrosis patients looking for a transplant, determining that the changesnin Covid-19 are driven not just by mutations in the virus but adaptations of human immune response, or other “bench to bedside” medical science, Fred Adler has found a home in the mechanistic aspects, the “how,” of basic science.

How to synthesize his research over the past thirty years is the next big question. For now he will continue with modeling biological systems, their signaling networks based on the body’s own network of “trust” between components, and determining how those systems are corrupted… and maybe how to fix them.

>> BACK <<


Theory Meets Intuition

Theory Meets Intuition

Will Feldman

Will Feldman, Assistant Professor of Mathematics, joined the Department of Mathematics in 2020. He studies mathematical models of physics and thinks about the things most of us take for granted, for example, fluid flow, water droplets, and flame propagation. These models are often developed by engineers or physicists using basic assumptions, but the resulting equations can be difficult or impossible to solve exactly.

“I’m interested in proving mathematically rigorous results for these models,” said Feldman. In his research, the results sometimes show the limitations of the modeling assumptions used to derive the equations. Other times, they explain the behavior of all the solutions of the equation without relying on special formulae. “And sometimes, the results are used to justify numerical computations, which are meant to approximate solutions of these equations,” he said.

One particular type of problem Feldman has studied is called “homogenization”—the study of the physical properties of complicated heterogeneous materials. The idea is to “average” or “homogenize” the complicated small-scale inhomogeneities in the material to derive simpler effective equations to describe properties at larger scales. For example, the ideas of homogenization theory can be used to study the shapes of water droplets on surfaces that have microscopic roughness, such as a plant leaf, a piece of glass, or a table top.

Water droplet on fabric.

“I like to work out these kinds of questions because I get to use both physical intuition and theoretical mathematical tools,” he said.
Feldman wasn’t always interested in mathematics. As an undergraduate, he thought he wanted to study physics or history. He started taking math classes because math was useful in studying advanced physics. “I had a lot of amazing math professors, and I started to like math a lot,” he said. “Eventually, I realized I could maybe study math and also bring in my interest in applications (especially physics). Basically, that’s how I ended up studying partial differential equations.”

Like many undergrads who study math, Feldman was worried he would need a special talent to succeed at math, but he had supportive and encouraging mentors, so he never got too discouraged. “I hope the experience of having good mentors has taught me to be a good mentor, too, and show my students I believe in them and the many interesting possibilities available in a career in or related to mathematics,” he said.

Before joining the U, Feldman received his Ph.D. from UCLA in 2015 and was an L.E. Dickson Instructor at the University of Chicago from 2015-2019. He was also a member at the Institute for Advanced Study (IAS) from 2019-2020. The IAS is one of the world’s leading centers for curiosity-driven basic research, based in Princeton, NJ.

In 2019, Feldman was awarded the John E. and Marva M. Warnock Presidential Endowed Chair for Mathematics by the University of Utah. He will hold the chair for five years and anticipates the funding will provide new and interesting directions for his research. He hopes to have a positive impact by training, mentoring, and supporting a next generation of mathematicians. “It was a great honor to be offered the Warnock Chair,” said Feldman. “I am obviously very proud to receive the award and grateful to the Warnock family and the university.”

As he moves forward in his research, he’s been thinking about problems involving interfaces in heterogeneous media. He’s also been wondering about transport equations and models of grain boundary motion in polycrystalline materials. He’s looking forward to discussions and collaborations with his colleagues in the Math Department, especially in the applied and probability groups.
Feldman and his wife are in the midst of raising two young children. He enjoys the great hiking in Utah and is looking forward to relearning how to ski and maybe starting new outdoor activities, such as climbing and biking. He enjoys cooking and has become obsessed (during the pandemic) with making a great cup of coffee.

- by Michele Swaner, first published at

Warnock Presidential Endowed Chair

“A Presidential Endowed Chair at the University of Utah is one of the highest honors that we can bestow on a faculty member.” —Dean Peter Trapa

Presidential Endowed Chairs are crucial for the recruitment and retainment of the most accomplished faculty members. Through these philanthropic gifts, the faculty are able to further support their cutting-edge research and explore new areas in their field.

John E. Warnock, BS’61, MS’64, PhD’69, and Marva M. Warnock created a Presidential Endowed Chair for Faculty Development in Mathematics in 2001 through a gift of Adobe Systems stock.

For more information on a establishing a Presidential Endowed Chair, or other named gift opportunities, please contact the development team at 801-581-6958, or visit

>> BACK <<


Space Plants

The Future of Space travel

Ming Hammond

For humanity to push the boundaries of space exploration, we’re going to need plants to come along for the ride. Not just spinach or potatoes, though—plants can do so much more than just feed us.

“There’s a lot of promise, potential and hope that we can use the tools developed in synthetic biology to solve problems.” says Chemistry Professor Ming Hammond, “not just that you would find in space, but where you have extreme limitation of resources.”

A synthetic garden.

Synthetic biology is a field that engineers biological systems. In this case, the team is looking at plants as potential bio-factories. Every organism naturally produces countless proteins as part of its biological function, so why not engineer a plant to produce, say, a needed medication or a polymer that could be useful in future long-term space exploration missions?

“The benefit is that you can take seeds with you,” Hammond said. “They’re very lightweight. They grow and gain biomass using the CO2 that we breathe out. And if those plants can produce proteins on demand—we know that plants are able to produce anti-viral and anti-cancer antibodies on a large scale.”

LED lights and USB camera.

Synthetic biology is already established on Earth. But translating that same technology to spaceflight requires different considerations. Hammond and her team encountered many of these constraints when adapting their experiment to operate within the small (10cm by 10cm) CubeSat enclosure.

For spaceflight, the team decided to engineer plants to change color as they produced the target protein, and monitor the progress with a camera. It’s an elegant and innovative solution, based on a previously published method, but adapted for the constraints of a cube in space.

Final assembly.

“We had to take something that worked beautifully in the most carefully controlled conditions,” Hammond said, “and get it to work under very harsh and challenging conditions inside the plant cube.”

The plant cube was designed with the forward vision of preparing for plant growth studies on the moon, and is a technology development step towards that goal.

The entire experiment took 10 days and appeared to show successful protein production. The results from the team, including collaborators from NASA Ames and International Space University, were published this year.

10x10cm experiment enclosure.

It takes a lot of time and effort to put equipment in space, and Hammond appreciates the many hours of work that the team has put in. “We are a small but dedicated group of volunteers,” she said. “People worked nonstop to fix last-minute things that came up before launch. I’m just really proud of the effort everyone’s put in.”

SpaceX Falcon 9 rocket.

Hammond and her family traveled to the NASA Kennedy Space Center to watch the Dec. 5, 2019 launch of her experiment, which was nestled within a SpaceX Falcon 9 rocket on a resupply mission to the International Space Station.

“At the launch of my experiment, we had a chance to see Bob Behnken and Doug Hurley, the two astronauts that flew the first manned SpaceX flight on May 30, 2020,” she said. “It was an amazing opportunity to share the launch with my son, (6 years old at the time), and other family members. Of all the things I’ve done in science this, for them, is the one that probably inspires the most interest and awe.”

By Paul Gabrielsen

>> BACK <<


The Frontier of Physics

The Frontier of Physics

The Standard Model of particle physics is the theory that explains how the most elementary particles interact with each other and combine to form composite objects, like protons and neutrons. Developed over the course of many decades, what we know as the Standard Model today was formulated nearly half a century ago and remains a focus of study for particle physicists. But by itself, the Standard Model fails to provide an explanation for many important phenomena, such as the existence of the dark matter in the universe.

The Standard Model

Today, physicists and researchers are on the frontier in the search for physics beyond the Standard Model, using connections between theoretical particle physics, cosmology, and astrophysics to help us understand the universe.

Pearl Sandick, Associate Professor of Physics and Astronomy and Associate Dean of Faculty Affairs for the College of Science, is on that frontier. As a theoretical particle physicist, she studies some of the largest and smallest things in the universe, including dark matter, which is the mysterious stuff that gravitationally binds galaxies and clusters of galaxies together.

While regular matter makes up about one-sixth of the total matter in the universe, dark matter makes up five-sixths. There are compelling arguments that dark matter might actually be a new type of elementary particle. Electrons are an example of an elementary particle—they are the most fundamental building blocks of their type and are not composed of other particles. Other examples of elementary particles include quarks, neutrinos, and photons.

In August 2019, Sandick and her colleagues hosted a workshop entitled “The Search for New Physics—Leaving No Stone Unturned,” which brought together dozens of particle physicists, astrophysicists, and cosmologists from around the world to discuss recent advances and big ideas. “It was such a vibrant environment; I think it helped us all broaden our perspectives and learn new things. Though there’s a lot going on in the meantime, we’re already excited about the prospect of hosting a second “No Stone Unturned” workshop in the new Science Building.”

Recently, Sandick has turned her attention to another cosmological phenomenon—black holes—tackling the question of how their existence affects our understanding of dark matter and other physics beyond the Standard Model.

“Some of this new research makes use of the cosmic microwave background (CMB), which is leftover radiation from the Big Bang that we can observe today,” said Sandick.

“CMB measurements can help us understand the structure and composition of the universe, including how much is made of dark matter. The CMB also can provide hints about what other particles or objects existed in the early universe.”

Before the CMB was created, the universe was very hot and very dense. In this environment, the densest places would have collapsed to become black holes. The black holes that formed in this way are called primordial black holes (PBHs), to differentiate them from black holes that form much later when stars reach the end of their lives. Heavy enough PBHs would still be around today and could make up some or all of the dark matter, providing an alternative to the idea that dark matter is a new particle. Lighter PBHs probably are not an explanation for dark matter, but they would have had an important interplay with dark matter and other new particles.

Sandick, along with a U of U postdoctoral associate, Barmak Shams Es Haghi, have been looking into the many impacts of a population of light PBHs in the early universe. Recently, they’ve completed the first precision study of some spinning PBHs in the early universe, finding that current CMB measurements from the Planck satellite (an observatory operated by the European Space Agency) and future measurements with the CMB Stage 4 experiment at the South Pole and in the Chilean desert are sensitive to many important PBH scenarios. The Planck data already point to some more and less likely possibilities, while CMB Stage 4 will be an important step forward in understanding the life and death of small black holes.

In addition to her research, Sandick is passionate about teaching, mentoring, and making science accessible and interesting. She has been recognized for her teaching and mentoring work, with a 2016 University of Utah Early Career Teaching Award and a 2020 University of Utah Distinguished Mentor Award. In 2020, she also was named a U Presidential Scholar. Women are still widely underrepresented in physics, and Sandick is actively involved in organizations that support recruitment, retention, and advancement of women physicists. She has served on the American Physical Society (APS) Committee on the Status of Women in Physics and as the Chair of the National Organizing Committee for the APS Conferences for Undergraduate Women in Physics. She is currently chair of the APS Four Corners Section, which serves approximately 1,800 members from the region. In 2011, she founded a group to support women in the Department of Physics and Astronomy and continues to serve as their faculty advisor.

She earned a Ph.D. from the University of Minnesota in 2008 and was a postdoctoral fellow at Nobel Laureate Steven Weinberg’s group (Weinberg Theory Group) at the University of Texas at Austin before moving to the University of Utah in 2011.

- by Michele Swaner, first published at

>> BACK <<