At the Environmental Molecular Sciences Laboratory (EMSL), computational researchers have taken a deep dive into exploring how artificial intelligence (AI) can support scientific discovery through examining processes and components at the smallest of scales. Researchers are using AI to identify proteins like never before using a new computational program called PeakDecoder, which was developed by EMSL Computational Scientist Aivett Bilbao. Through Model-Experiment (ModEx) integration, they are integrating experimental measurements (e.g., soils, rhizosphere, and biologic and anthropogenic emissions) into computational and modeling frameworks either directly for scale-appropriate models or through parameterizations. Researchers are also using AlphaFold to make protein structure predictions, just to name a few.
Through the EMSL User Program, scientists from around the world are also working with staff researchers and a range of EMSL computational technologies to expedite scientific discovery through AI. This year, one such user project led by Pernilla Wittung-Stafshede, a professor at Chalmers University of Technology in Sweden, is using AI to identify how proteins fold—a feat that has stumped scientists for years.
Read the full transcript of the EMSL Podcast “Bonding Over Science” on the EMSL website.
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