
Biography
Matthew is a BBSRC iCASE PhD student where together with BenevolentAI, Matthew is developing machine learning (ML) and systems biology approaches to investigate the role of the microbiome during the ageing process.
By harnessing the power of ML, these approaches will be used to identify prognostic indicators from metagenomics and metatranscriptomics data. Combining ML-based features with host-microbiome interactions and systems biology, we aim to improve our understanding of how the microbiota contributes to our health.
Matthew started his research at the Earlham Institute during the second year of undergraduate studies where he was introduced to systems biology. As an intern within the Korcsmáros Group, he developed an algorithm to identify and contextualise autophagy-related proteins within a molecular interaction network.
This experience led to his final year research project, in which he created an integrated network-medicine and ML pipeline to identify prognosis indicators in ulcerative colitis. These short-term projects gave him the motivation and passion to further explore the capabilities of ML within life sciences.
Publications
Related reading.

Finding fungi at the fen

The genetic machinery that drives biodiversity

On the origin of errors: the causes and consequences of mistakes during DNA replication

Could long-read RNA sequencing be the future of drug discovery?

Why is genome annotation important?

Why cloud computing is important for data-driven bioscience research

How bioinformatics can crack the complex case of protist biodiversity

The dramatic effects genomics will have on our future world

Key tilapia genome offers boost to global food security

Exotic wheat DNA could help breed ‘climate-proof’ crops

Sequencing project to unleash the huge potential of euglenoids

Circadian clock insights could be key to increased wheat yields

European consortium launched to reverse biodiversity loss through genomics research

Tracking bacterial evolution in real time spots emergence of antimicrobial resistance

Big Data initiative awarded £6.3 million as part of major UKRI investment in research infrastructure

Not all looks rosy for the pink pigeon
