Andrea Rodriguez Delherbe

My doctoral training focuses on implementing computational models based on diverse machine learning techniques and high-performance computing to study the principles of gene regulation across evolution and species. Within the scientific context of developmental biology in zebrafish and chicken embryos, I am currently studying the impacts of chromatin architecture dynamics on gene regulation throughout the different developmental stages using transfer-learning methods. In addition, I am using transformer-based networks to unveil motifs, with a potential cis-regulatory role, that highly impact the underlying decision-making process in predicting open chromatin in red blood cells.

Before joining the RDM D.Phil in Medical Sciences program, I obtained a BSc in Computer Science at Universidad Tecnica Federico Santa Maria, Chile, where I worked as a research assistant in implementing machine learning models to answer diverse scientific questions in the fields of biomedical imaging, bioinformatics, astronomy, and particle physics.

My academic goal is to become a genomics data scientist focused on developing and applying machine learning algorithms to answer biological questions that contribute to developmental biology, physiology, immunology, and/or oncology.