Simulating the Natural World

Age-related skeletal muscle loss (sarcopenia) is a leading cause of impaired physical function and health in older adults. Resistance exercise (RE) represents a promising strategy to counteract sarcopenia. However, older muscle does not grow as well as younger muscle in response to RE, and exactly why remains unclear. This talk will focus on using gene networks to predict molecules that may be key to exercise-induced muscle adaptation in young and older adults, which may hold promise as therapeutic targets for optimising exercise strategies to promote a healthy muscle mass across the lifespan.

Fungi, such as yeast, moulds and mushrooms, are everywhere. They live in soil, on plants and some even live on and inside us. A few species of fungi can cause serious human infections that can be lethal, killing more people around the world than malaria. To make things worse, there are no vaccines to protect against fungal infections and treating these infections can be difficult. In my talk, I’ll show how biological data can be used to generate computer models that simulate infectious fungi. I’ll also show how these models can inform experiments to learn new things about biology.

Each day, human skin is exposed to dangerous UV light from the Sun. As a result of this, non-melanoma skin cancer (NMSC) is the most common form of cancer worldwide. NMSC is currently treated with surgical excision, which is both expensive and can leave patients with cosmetic damage. However, Photodynamic Therapy (PDT) is an alternative treatment option which allows for cost effective treatment whilst achieving excellent cosmetic results. In this talk we will discuss our work on PDT using astrophysics inspired computer modelling combined with clinical data, to help improve treatment outcome.