Matthew Madgwick

Postgraduate Student

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Systems Biology of Gut-Microbe Interactions

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I am a BBSRC iCASE PhD student within the Korcsmáros group, where together with BenevolentAI, I am 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.

I started my research at the Earlham Institute during the second year of undergraduate studies which introduced me to systems biology. As an internship within in the Korcsmáros Group, I developed an algorithm to identify and contextualise autophagy-related proteins within a molecular interaction network. This experience led to my final year research project, in which I created an integrated network-medicine and ML pipeline to identify prognosis indicators in ulcerative colitis. My experience from these short-term projects gave me the motivation and passion for capabilities of ML within life sciences.

Treveil A,Bohar B,Sudhakar P,Gul L,Csabai L,Olbei M,Poletti M,Madgwick M,Andrighetti T,Hautefort I,Modos D,Korcsmaros T. (2021)

ViralLink: An integrated workflow to investigate the effect of SARS-CoV-2 on intracellular signalling and regulatory pathways

PLoS Computational Biology


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Seyed Tabib N., Madgwick M., Sudhakar P., Verstockt B., Korcsmaros T., Vermeire S.. (2020)

Big data in IBD: big progress for clinical practice.

Gut


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