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Molecular dynamics simulations generate vast amounts of valuable but chaoticaly organized data. Unlike static structures in curated repositories such as PDB or AlphaFold DB, MD data are scattered across general-purpose platforms with little metadata, poor searchability, and no tailored visualization or analysis tools. This presentation explores the current messiness of molecular dynamics data and the steps being taken to bring order by automatic metadata extraction, biomolecule identification, repository development, and federated search. By making MD datasets FAIR (Findable, Accessible, Interoperable, Reusable), we are not only addressing today’s needs but also preparing the ground for future, as-yet-unknown applications, including AI-driven discovery.
