Novel Bioinformatics and AI approaches for microbiome analysis

The microbiome, the collective genomic entity of all microbiota – bacteria, archaea, fungi, protozoa, and viruses of an environment holds an immense amount of information, a considerable amount of improvement with respect to data analysis and real-time interpretation is still needed to bring research out of the lab and into everyday usage in the built environment, our homes, places of work and health systems. Collectively the microbiota, which we initially acquire at birth, have a huge lifelong impact on health defining our gut ecosystem, and impact on complex health problems such as: mental-health, cancer, neurodegenerative and autoimmune diseases. Humans encounter and pass on microbiota from one and other and their environment, including the built environment of constructed buildings. Optimal and timely analysis and information extraction from the microbiome is a key hurdle in leveraging it to effetely improve human and environmental health.

This project will focus on developing novel bioinformatics approaches for real-time and in-depth functional analysis of the microbiome from meta- genomics/transcriptomics data, including long read sequencing, and translating these into informing our relationships with our built environment for improved health and environmental sustainability. The aim of the project is to utilise cutting edge Artificial Intelligence and Machine/Deep Learning techniques to enable faster and deeper analysis of data rich microbiomes.