https://aiscience.uk/tags/biology/ Recent content in Biology on AI Science Report Hugo en-us Thu, 09 Jul 2026 00:00:00 +0800 https://aiscience.uk/posts/abicl-in-context-learning-antibody-affinity-ranking/ Thu, 09 Jul 2026 00:00:00 +0800 https://aiscience.uk/posts/abicl-in-context-learning-antibody-affinity-ranking/ <p>In 2023, the world spent over $200 billion on antibody drugs — treatments like Keytruda for cancer and Humira for autoimmune disease. But finding a single antibody that binds well enough to become a drug is like searching for a specific grain of sand on a beach. A typical drug discovery campaign screens thousands of candidates, each one requiring expensive lab tests to measure how tightly it grabs its target. Most fail.</p> https://aiscience.uk/posts/genetic-toggle-switch-fate-division/ Wed, 17 Jun 2026 00:00:00 +0800 https://aiscience.uk/posts/genetic-toggle-switch-fate-division/ <p>Every minute, millions of your cells face a decision. A stem cell in your bone marrow must choose: become a red blood cell or a white one? An immune cell must decide: multiply to fight an infection, or quietly self-destruct? A cell in a developing embryo must pick its destiny: skin, nerve, or muscle?</p> <p>For decades, biologists have modelled these life-or-identity decisions using a beautifully simple idea called the genetic toggle switch — two genes that mutually inhibit each other, locking a cell into one stable state or another. It is one of the most famous concepts in molecular biology, taught in textbooks and used to understand everything from embryonic development to cancer. But a new mathematical analysis from the University of Edinburgh, published this week, reveals a blind spot in this iconic model that may have been quietly misleading researchers for years. The problem? The way we&rsquo;ve been modelling cell division.</p>