Microbiome in Health & Disease MSc

Our Microbiome in Health & Disease MSc provides students with a unique background in all aspects of both analysis of microbiome and determining the role of microbiome in pathology with experience in both computational and experimental techniques.<br/><br/>Designed and delivered by the Centre for Host-Microbiome Interactions (CHMI) at King’s, the course brings together teaching in systems biology and bioinformatics with molecular biology, microbiology, immunology and physiology.<br/><br/>**Key benefits**<br/>- Deep understanding of microbial communities and their impact on host health and disease.<br/><br/><br/>- Focus on translation in clinical, agricultural and environmental challenges.<br/><br/><br/>In the post-human genome project world, our health is dependent on more than our genes. High throughput sequencing reveals the amazing complexity and extent of the microbial communities that reside within or upon us. We are also beginning to understand just how dynamic the interactions between the host and members of communities are. Interactions are diverse, and variations observed between individuals depend on a multitude of microbial and host factors, including diet and inflammatory status. More importantly, it is becoming clear that different disease states are linked to significant changes in the make-up of these communities. Scientists who understand the computational analysis of the huge data sets for microbial communities, and who are also able to interpret findings in the context of human and microbial health, will be in demand across this emerging field in academia and in industry.<br/><br/>**Course purpose**<br/><br/>The course aims to develop students knowledge of the microbial communities that reside within or upon us, and how they impact our health and disease processes.<br/><br/>It is designed for students who wish to improve their background knowledge and skills prior to applying for a PhD studentship, and also for students who wish to enhance their knowledge and skill set for analysing and interpreting the large, multiple omics data sets that are involved in microbiome research.