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Agentic genomics: Your science, made executable

Manuel Corpas, INFLAMomx Training School, University of Salerno, 7 September 2026.

This lecture asks what changes when a scientist can express a biological question in a form that an AI agent can help execute. It uses real RNA-seq and single-cell examples to show how scientific intent becomes an inspectable result, and why clinical-grade agentic genomics requires deterministic execution, traceable evidence, validation and equity.

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Three ideas to remember

  1. Agentic execution is now a question of when, not if.
  2. Early adoption gives scientists a chance to shape the field while its methods are still forming.
  3. The language of agents is context engineering: question, data, design, stopping rules and evidence.

Examples in the lecture

  • A paired dexamethasone RNA-seq analysis using four donor-derived airway smooth-muscle cell lines.
  • A deliberately invalid control that stops without producing a differential-expression result.
  • Recovery of the published STMN2 response after TDP-43 depletion.
  • A public PBMC3k single-cell workflow, with marker evidence treated as a hypothesis rather than a finished cell identity.
  • A benchmark showing that authored scientific rules and deterministic execution contribute different kinds of value.
  • An equity question: whose science is missing from the validation?

ClawBio is an open-source scientific commons for inspectable biological AI skills. As checked on 7 September 2026, the public repository had 1,126 stars, 261 forks and 48 commit-contributor accounts.

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