<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-07-08T08:44:08Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/D12CE055-6282-4328-9950-35B9D48C4745" ns1:id="D12CE055-6282-4328-9950-35B9D48C4745"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/ED9C72E5-699F-4EF5-A26E-41D890608333" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/FADF7D6D-1CAC-4A55-9952-9422142E88B9" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/FADF7D6D-1CAC-4A55-9952-9422142E88B9" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2026-04-29T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/1D7F45CA-E6A9-4406-B865-B580517B73C2" ns1:rel="FUND" ns1:start="2025-11-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10170024</ns2:identifier></ns2:identifiers><ns2:title>AI-Powered Discovery of Structured RNAs</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Fast Start Response</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>RNA molecules play a central role in the biology of all living things, but we've only scratched the surface in understanding their full potential. While DNA stores genetic instructions, RNA molecules are the dynamic players that help cells interpret, regulate, and respond to their environments. Many RNAs act like molecular switches or sensors, making them promising building blocks for the next generation of bio-based tools and therapies.

This project combines Artificial Intelligence (AI) and Engineering Biology to build a new discovery platform that reveals previously hidden RNA structures across genomes. These structures are often overlooked by traditional methods, but with recent advances in machine learning and access to millions of genomes, we now have the opportunity to uncover and harness them at scale.

This project builds on decades of scientific leadership in RNA biology and bioinformatics. Leveraging our experience developing Rfam, a globally recognised RNA database, we will train a next-generation AI model to detect structured RNAs across diverse species. This model will uncover novel RNA candidates with potential applications in therapeutics and synthetic biology, including the design of biological sensors, molecular controllers, and innovative treatments for rare diseases, viral infections, and antibiotic-resistant bacteria.

By combining cutting-edge AI tools with deep biological knowledge, the platform will reduce the time, cost, and complexity of developing RNA-based technologies. It will provide a foundation for researchers and biotech companies to create more sustainable, programmable biological systems, with potential applications in healthcare, agriculture, and industrial biotechnology.

This six-month project will be carried out entirely in the UK. The work will involve both in-house development and collaboration with a specialist AI subcontractor. By the end of the project, we will produce a minimum viable product: a working prototype of the RNA discovery platform, along with validation results showing its accuracy and usefulness.

Our long-term goal is to make this platform the engine behind a new wave of RNA-driven innovation. By enabling faster and more accessible RNA discovery, we aim to support the growth of the UK bioeconomy and position our company as a key player in the field of synthetic biology.</ns2:abstractText></ns2:project>