Tag: Modeling

Cloudy With a Chance of Scientific Discoveries


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.

Hands typing on a laptop with a digitized cloud and computer icons floating above them.
Credit: iStock.

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.

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More Than 25 Years of Competition and Collaboration Advance the Prediction of Protein Shapes


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.

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Year in Review: Our Top Three Posts of 2020


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!

The Science of Infectious Disease Modeling

Oblong light-blue structures with red spots in the middle connected to the surface of a sphere. 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.

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Learn Directly From Scientists Through Available Webinar Series


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.

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The Science of Infectious Disease Modeling

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What Is Computer Modeling and How Does It Work?

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.

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Revealing a Piece of Cilia’s Puzzle

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A multicolored tube made up of small dots with three sets of appendages attached along its length. 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.

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Advances in 3D Printing of Replacement Tissue

A bioprint of the small air sac in the lungs with red blood cells moving through a vessel network supplying oxygen to living cells. Credit: Rice University. A bioprint of the small air sac in the lungs with red blood cells moving through a vessel network supplying oxygen to living cells. Credit: Rice University.

A team of bioengineers, funded in part by NIGMS, has devised a way to use 3D bioprinting technology to construct the small air sacs in the lungs and intricate blood vessels. Continue reading “Advances in 3D Printing of Replacement Tissue”

Amazing Organisms and the Lessons They Can Teach Us

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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.

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Interview With a Scientist – Rommie Amaro: Computational and Theoretical Model Builder


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.

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Online Virus Tracking Tool Nextstrain Wins Inaugural Open Science Prize

Nextstrain’s analysis of the genomes from Zika virus obtained in 25 countries over the past few years. 

Credit: Trevor Bedford and Richard Neher, nextstrain.org.

Over the past decade, scientists and clinicians have eagerly deposited their burgeoning biomedical data into publicly accessible databases. However, a lack of computational tools for sharing and synthesizing the data has prevented this wealth of information from being fully utilized.

In an attempt to unleash the power of open-access data, the National Institutes of Health, in collaboration with the Howard Hughes Medical Institute and Britain’s Wellcome Trust, launched the Open Science Prize Exit icon. Last week, after a multi-stage public voting process, the inaugural award was announced. The winner of the grand prize—and $230,000—is a prototype computational tool called nextstrain Exit icon that tracks the spread of emerging viruses such as Ebola and Zika. This tool could be especially valuable in revealing the transmission patterns and geographic spread of new outbreaks before vaccines are available, such as during the 2013-2016 Ebola epidemic and the current Zika epidemic.

An international team of scientists—led by NIGMS grantee Trevor Bedford of the Fred Hutchinson Cancer Research Center, Seattle, and Richard Neher Exit icon of Biozentrum at the University of Basel, Switzerland—developed nextstrain as an open-access system capable of sharing and analyzing viral genomes. The system mines viral genome sequence data that researchers have made publicly available online. nextstrain then rapidly determines the evolutionary relationships among all the viruses in its database and displays the results of its analyses on an interactive public website.

The image here shows nextstrain’s analysis of the genomes from Zika virus obtained in 25 countries over the past few years. Plotting the relatedness of these viral strains on a timeline provides investigators a sense of how the virus has spread and evolved, and which strains are genetically similar. Researchers can upload genome sequences of newly discovered viral strains—in this case Zika—and find out in short order how their new strain relates to previously discovered strains, which could potentially impact treatment decisions.

Nearly 100 interdisciplinary teams comprising 450 innovators from 45 nations competed for the Open Science Prize. More than 3,500 people from six continents voted online for the winner. Other finalists for the prize focused on brain maps, gene discovery, air-quality monitoring, neuroimaging and drug discovery.

nextstrain was funded in part by NIH under grant U54GM111274.