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Biomolecules constantly change shape, but many biologically important processes occur too slowly to be captured by conventional molecular simulations. Gen-COMPAS uses AI to identify rare molecular events, discover intermediate structures, and reconstruct transition pathways. Using computing resources accessible to most research groups and NAMD, it revealed an intermediate state for a complex membrane protein that was subsequently validated experimentally. Rather than moving molecules faster, Gen-COMPAS learns where to look, opening new ways to uncover how molecular machines make life possible. Read more in a recent paper in Nature by Chipot and colleagues.

Editorials

The Future of Biomolecular Modeling

A 2015 TCBG Symposium brought together scientists from across the Midwest to brainstorm about what's on the horizon for computational modeling. See a summary of what these experts foresee. Read more

Computational Biology of Membrane Proteins

Since 1988 Illinois researchers have consistently honed their skills in parallel computing, which enabled them to elucidate dynamic processes occurring in many membrane proteins and produce exciting discoveries. By Lisa Pollack Read more

Announcements

  • Research Scientist Position
  • Workshop on Computational Biophysics 2026
  • Cade Duckworth awarded prestigious 2026-27 MCB/Biophysics Graduate Fellowship
  • Yupeng Li-Beckman Institute Graduate Fellow


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    A "neural gas" network learns topologies. Artificial Neural Networks, pp. 397-402. Elsevier, Amsterdam,   
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