Dr. Lucile Neyton is a bioinformatics programmer at the University of California, San Francisco. She completed her PhD in Precision Medicine at The University of Edinburgh, focusing on integrated systems biology of multiple organ dysfunction in acute pancreatitis.

In her current position, she investigates heterogeneity in critically ill patients. Her research focuses on identifying molecular subtypes and endotypes in acute respiratory distress syndrome (ARDS), sepsis, and other critical illnesses through advanced computational approaches.

Dr. Neyton has expertise in analyzing high-dimensional omics data, including genomics, bulk and single-cell transcriptomics, proteomics, and metabolomics. She designs machine learning models to predict disease states and identify gene expression signatures that distinguish patient subphenotypes. Through this work, she has revealed generalizable biological mechanisms across critical illness syndromes and identified candidate therapeutic targets through integrated multi-omics analysis.

With strong proficiency in R and Python, Dr. Neyton develops bioinformatics pipelines and analytical algorithms for complex biological datasets.