Rate My Professor Sarah Ennis

Ennis's research specializations include inflammatory bowel disease, big data, genomics, next-generation sequencing for clinical diagnostics, and rare diseases. She integrates genomic, transcriptomic, and clinical data using computational methods including machine learning and large language models to identify disease mechanisms and novel genetic variants for personalised medicine. She created the GenePy algorithm for gene-level pathogenicity scoring, identifying over 120 missed diagnoses in national datasets and deployed in Genomics England and UK Biobank. As Chief Investigator of the Genetics of Inflammatory Bowel Disease Study, she has recruited nearly 3,000 patients, generating over 50 publications. She has approximately 200 peer-reviewed publications, including "HiFi long-read RNA sequencing enhances clinical diagnostics in rare disorders" (2026), "Application of generative artificial intelligence to utilise unstructured clinical data for acceleration of inflammatory bowel disease research" (2026), "Rare variants in embryonic development and cell signalling genes in syndromic and non-syndromic orofacial clefts" (2026), and "Cardiomyopathies in 100,000 Genomes Project: interval evaluation improves diagnostic yield and informs strategies for ongoing gene discovery" (2024). She is Research Director within NHS England’s Genomic Medicine Service, founding member of the Genomic Artificial Intelligence Network, Genomics Lead for Wessex Health Partners, and advisor to national policy bodies. Her work is cited in 28 government policy documents, and she delivers keynote talks at conferences including Festival of Genomics & Biodata, European and American Societies of Human Genetics.