The UCL Division of Biosciences conducts world-leading research in computational biology, integrating mathematics, computer science and life sciences. Our work spans machine learning, modelling and simulation, computational neuroscience, structural biology, genetics and biomedicine. By combining advanced computational methods with experiments and data, we turn complex biological observations into mechanistic insight, predictive models, and real-world impact across health, disease, and nature.

Discover our research, impact and teaching in this area.

Computational foundations and machine learning
computer software

Computational foundations and machine learning

Developing new algorithms for data analysis.

Modelling, simulation and complex systems
abstract network

Modelling, simulation and complex systems

Developing new models of complex biological systems.

Computational neuroscience and cognition
brain with circuitry

Computational neuroscience and cognition

Using mathematical models to understand cognition.

Structural biology and computational biochemistry
structural biology

Structural biology and computational biochemistry

Computational modelling and analysis of protein structure and reaction pathways.

Computational genetics
teal DNA sequence

Computational genetics

Developing tools for the large-scale analysis of genes and genomes.

Computational biomedicine and biomedical engineering
colourful patches

Computational biomedicine and biomedical engineering

Using computational approaches to to study physiology and improve healthcare.

Computational ecology and biodiversity
landscape with hills and flying birds

Computational ecology and biodiversity

Developing quantitative tools to understand biodiversity, ecosystems, and global change.

Explore our AI and Machine Learning Research

Biosciences AI and Machine Learning
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Biosciences AI and Machine Learning

UCL Biosciences combines AI with expertise in biology, computing, maths and physics to advance research in genomics, neurobiology and health, accelerating discovery across life sciences.