Adam Gormley, Ph.D., describes himself as a creative and adventurous person—albeit, not creative in the traditional sense. “Science allows me to be creative; to me, it’s a form of art. I love being outdoors, going on sailing trips, and spending time adventuring with my family. Research is the same—it’s an adventure. My creative and adventurous sides have combined into a real love for science,” he says. Dr. Gormley currently channels his passion for science into his position as an assistant professor of biomedical engineering at Rutgers University in Piscataway, New Jersey.
Learning How the World Works
Both of Dr. Gormley’s parents worked in science and medicine—his mother as a medical doctor and his father as a physician-scientist—and they instilled in him a curiosity for how the world worked. When he was young, Dr. Gormley and his parents would tinker with cars or boats and fix broken household items together, all the while talking about the individual parts and how they functioned as a whole. “I always had that technical, hands-on side of me,” he says.
When she started college, Anne Carpenter, Ph.D., never guessed she’d one day create software for analyzing images of cells that would help identify potential medicines and that thousands of researchers would use. She wasn’t planning to become a computational biologist, or even to focus on science at all, but she’s now an institute scientist and the senior director of the Imaging Platform at the Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard in Cambridge.
Starting Out in Science
Before beginning her undergraduate studies at Purdue University in West Lafayette, Indiana, Dr. Carpenter’s strongest interests were reading and writing. Then, her subjects expanded. “In college, I liked science as much as anything else, and I realized that was unusual, as a lot of other people really struggled with it. I decided to pursue science because I enjoyed it and the field had good job prospects,” she says. Dr. Carpenter majored in biology because she felt it had the “juiciest questions” as well as a direct impact on human health.
“Science provides adventure and excitement every single day. When you’re pushing boundaries, you get to jump into the abyss of new areas. It can be scary, but it’s an incredible opportunity to try to improve our world and people’s lives,” says César de la Fuente, Ph.D., a Presidential Assistant Professor in the Perelman School of Medicine and School of Engineering and Applied Science at the University of Pennsylvania, Philadelphia. Our interview with Dr. de la Fuente highlights his journey of becoming a scientist and his research using artificial intelligence to discover new drugs.
Q: How did you first become interested in science?
A: I’ve always been fascinated by the world around me. I grew up in a town in northwest Spain, right on the Atlantic Ocean. As a kid, I would go to the beach to investigate marine organisms and bring home all sorts of different fish to study. My mom wasn’t too happy about that! We’re all born scientists, but we tend to lose that curiosity as we enter adulthood. The key is to not lose our ability to learn every day.
The cloud. To many, it’s a mysterious black hole that somehow transports photos and files from their old or lost phone to their new one. To some researchers, though, it’s an invaluable resource that allows them access to data analytics tools they wouldn’t otherwise have.
Scientists have begun using cloud computing to store, process, and analyze their data through online bioinformatics tools. Biological data sets are often large and hard to interpret, requiring complex calculating instructions—or algorithms—to understand them. Fortunately, these algorithms can run on local computers or remotely through cloud computing.
One advantage of cloud-based programs over local computers is the ability to analyze data without taking up the user’s personal storage space. With cloud-based storage, researchers can store their large data files, including their labeled notes called annotations. Another benefit is that users have easy access to software packages within the cloud for data analysis. The cloud also encourages collaboration among scientists by making it easy to share large amounts of data.
Dr. Brian Munsky. Credit: Colorado State University.
“I think having a career in science is really the best way to rechannel the inner child, to remain forever curious about the world,” says Brian Munsky, Ph.D., an associate professor of chemical and biological engineering at Colorado State University, Fort Collins. Check out the highlights of our interview with Dr. Munsky below to learn how his childhood practical jokes led to him running a research group that uses computational and experimental methods to study complex processes inside cells.
“You’re not going to be able to do biology without understanding programming in the future,” Melissa Wilson, Ph.D., an associate professor of genomics, evolution, and bioinformatics at Arizona State University, said in her 2019 NIGMS Early Career Investigator Lecture. “You don’t have to be an expert programmer. But without understanding programming, I can assert you won’t be able to do biology in the next 20 years.”
A growing number of researchers, like Dr. Wilson, are studying biology using computers and mathematical methods. Some of them started in traditional biology or other life science labs, while others studied computer science or math first. Here, we’re featuring two researchers who took different paths to computational biology.
Recent news headlines are awash in references to “modeling the spread” and “flattening the curve.” You may have wondered what exactly this means and how it applies to the COVID-19 pandemic. Infectious disease modeling is part of the larger field of computer modeling. This type of research uses computers to simulate and study the behavior of complex systems using mathematics, physics, and computer science. Each model contains many variables that characterize the system being studied. Simulation is done by adjusting each of the variables, alone or in combination, to see how the changes affect the outcomes. Computer modeling is used in a wide array of applications, from weather forecasting, airplane flight simulation, and drug development to infectious disease spread and containment.
Sohini Ramachandran, Brown University. Credit: Danish Saroee/Swedish Collegium for Advanced Study.
Recent advances in computing enable researchers to explore the life sciences in ways that would have been impossible a few decades ago. One new tool is the ability to sequence genomes, revealing people’s full DNA blueprints. The collection of more and more genetic data allows researchers to compare the DNA of many people and observe variations, including those shared by people with a common ancestry.
Sohini Ramachandran , Ph.D., is director of the Center for Computational Molecular Biology and associate professor of biology and computer science at Brown University in Providence, Rhode Island. She is also a recent recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE). Dr. Ramachandran researches the causes and consequences of human genetic variations using computer models. Starting with genomic data from living people, her lab applies statistical methods, mathematical modeling, and computer simulations to discover how human populations moved and changed genetically over time.
Many researchers who search for anti-cancer drugs have labs filled with chemicals and tissue samples. Not Rommie Amaro. Her work uses computers to analyze the shape and behavior of a protein called p53. Defective versions of p53 are associated with more human cancers than any other malfunctioning protein.