If you want to research historical events for a college essay, learn about tropical fish, or even translate text into a different language, you can type keywords into an internet search engine and get almost instant results drawn from diverse, international sources on that subject.

Unfortunately, it’s not so easy for the scientist trying to find solutions for the COVID-19 pandemic. Even though researchers across the world have already amassed a wealth of information about the disease and continue to reveal new insights every day, this valuable data is stored in different digital libraries, organized in different structures, and written with different jargon. To get the most out of our collective COVID-19 knowledge, someone needs to collect it all in one place.

And that’s precisely what a team led by Berkeley Lab is doing, using bioinformatics and machine learning.

Natalia Molchanova, a scientific engineering associate at the Molecular Foundry, works on synthetically produced proteins called peptoids, which have advanced low-cost biotech solutions.