AI In Biology

Project

Digital Twin Cell

Creating a digital replica of a living cell enabling researchers to perform virtual experiments and gain valuable insights into cell biology.

Project

Disease X

The World Health Organisation lists Disease X (the name for a currently unknown pathogen that could cause a future epidemic) as a very serious threat to human health. To prepare for Disease X, we are building a pipeline to rapidly identify, and test nanobodies, for detecting and potentially treating future viral diseases

Platform

Nanobodies Discovery Platform

Nanobodies are single domain antibodies derived from the unique heavy chain only immunoglobulins of camels, llamas, and alpacas.

PhD Project Area

Biological Data Science

How could we build cutting-edge AI tools to translate biological data into solutions and guide better decision-making?

Life Science Challenge

Emerging Interest Area: Cell-cell Interactions

The Franklin’s Emerging Interest Areas are developing areas of research led by our talented emerging leaders. These areas align with the Franklin’s mission of accelerating life science discovery and improving human health.

Science update

Moving from cells into tissue: a new tomography method

Researchers led by Dr Michael Grange at the Rosalind Franklin Institute have developed a robust molecular imaging workflow for brain tissue samples. Their approach utilises plasma ion beams, which increased the size of samples that could be extracted for imaging,…

Science update

Using AI to improve the analysis of 3D biological images

Scientists have developed a new machine learning model, known as Affinity-VAE, that improves the analysis of 3D biological images in fields such as cryo-electron tomography (cryo-ET). By making use of prior knowledge about protein structures, the model can identify clusters…