The power of computer code has been a longtime fascination for Tomas Helikar, Ph.D., a professor of biochemistry at the University of Nebraska-Lincoln (UNL). In college, when he learned he could use that power to help researchers better understand biology and improve human health, Dr. Helikar knew he’d found his ideal career. Since then, he’s built a successful team of scientists studying the ways we can use mathematical models in biomedical research, such as creating a digital replica of the immune system that could predict how a patient will react to infectious microorganisms and other pathogenicinsults.
A Career in Computational Biology
Dr. Helikar first became involved in computer science by learning how to build a website as a high school student. He was amazed to learn that simple lines of computer code could be converted into a functional website, and he felt empowered knowing that he had created a real product from his computer.
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.
Proteins (such as hemoglobin, actin, and amylase) are workhorse molecules that contribute to virtually every activity in the body. Some of proteins’ many jobs include carrying oxygen from your lungs to the rest of your body (hemoglobin), allowing your muscles to move (actin and myosin), and digesting your food (amylase, pepsin, and lactase). All proteins are made up of chains of amino acids that fold into specific 3D structures, and each protein’s structure allows it to perform its distinct job. Proteins that are misfolded or misshapen can cause diseases such as Parkinson’s or cataracts.
While it’s straightforward to use the genetic code to predict amino acid sequences of proteins from gene sequences, the vast diversity of protein shapes and many factors that influence a protein’s 3D structure make it much more complicated to create simple folding rules that could be used to predict proteins’ structures from these sequences. Scientists have worked on this problem for nearly 50 years, and NIGMS has supported many of their efforts, including the Critical Assessment of Structure Prediction (CASP) program.
Over the year, we dove into the inner workings of cells, interviewed award-winning researchers supported by NIGMS, shared a cool collection of science-themed backgrounds for video calls, and more. Here, we highlight three of the most popular posts from 2020. Tell us which of this year’s posts you liked best in the comments section below!
Spike proteins on the surface of a coronavirus. Credit: David Veesler, University of Washington.
What does “modeling the spread” (or “flattening the curve”) mean, and how does it apply to infectious diseases such as COVID-19? Learn about the science of infectious disease modeling and how NIGMS supports scientists in the field.
Looking for more virtual learning opportunities? NIGMS recently recorded a series of 14 webinars where experts shared their knowledge on topics from infectious disease modeling to pursuing a career in biomedical science. With the start of the 2020-2021 academic year, we’re highlighting a webinar that’s particularly relevant for our Biomedical Beat readers who are educators. You can check out the whole series on the NIGMS YouTube channel.
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.
A partial model of a doublet microtubule. Credit: Veronica Falconieri.
Cilia (cilium in singular) are complex organelles found on all of our cells except red blood cells. Their rhythmic beating moves fluid or materials over the cell to help transport food and oxygen or remove debris. For example, cilia in our windpipe prevent bacteria and mucous from traveling to the lungs. Some pick up signals like antennae, such as cilia in our ears that help detect sounds. One component of cilia is the doublet microtubule, a major part of cilia’s skeleton that gives it strength and rigidity.
What do you have in common with rodents, birds, and reptiles? A lot more than you might think. These creatures have organs and body systems very similar to our own: a skeleton, digestive tract, brain, nervous system, heart, network of blood vessels, and more. Even so-called “simple” organisms such as insects and worms use essentially the same genetic and molecular pathways we do. Studying these organisms provides a deeper understanding of human biology in health and disease, and makes possible new ways to prevent, diagnose, and treat a wide range of conditions.
Historically, scientists have relied on a few key organisms, including bacteria, fruit flies, rats, and mice, to study the basic life processes that run bodily functions. In recent years, scientists have begun to add other organisms to their toolkits. Many of these newer research organisms are particularly well suited for a specific type of investigation. For example, the small, freshwater zebrafish grows quickly and has transparent embryos and see-through eggs, making it ideal for examining how organs develop. Organisms such as flatworms, salamanders, and sea urchins can regrow whole limbs, suggesting they hold clues about how to improve wound healing and tissue regeneration in humans.
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.