Computational Biology

Computational Biology applies mathematical modelling, statistics, and machine learning to understand biological systems through data. It connects quantitative methods with biological questions in areas such as genomics, structural biology, biomedical imaging, and systems biology. The aim is to extract meaningful patterns from complex biological data and turn them into scientific insight.

At IE, research in Computational Biology focuses on developing computational tools to analyse high-dimensional and structured biological data. This includes work on protein structure, cryo-electron microscopy, biomolecular modelling, image analysis, and predictive models for biological and medical applications. Researchers also study how to combine mechanistic understanding with data-driven methods to improve inference, interpretation, and prediction.

This research has strong relevance for health and life sciences. Applications include drug discovery, precision medicine, disease modelling, and the study of cellular and molecular processes. By integrating biology with mathematics, statistics, and AI, Computational Biology helps address important questions in medicine and biotechnology.