Bioinformatics
Bioinformatics analysis enables fundamental understanding of biological mechanisms and may suggest pathways to improved treatment of disease."
Prof Timothy Ebbels
Head of Section
Bioinformatics is an interdisciplinary field that combines computational and visualisation methods to model and extract knowledge from complex biological, biochemical and clinical data. Modern data science methods such as (multivariate) statistics, machine learning and artificial intelligence allow modelling, analysis, prediction and visualization of ‘Big Data’ derived from a plethora of experimental approaches.
Our data comes from a variety of techniques from genomics to metabolomics through to imaging and clinical diagnostics. A key activity is developing and adapting novel mathematical and statistical algorithms and software to analyse and integrate these diverse data sets to develop software platforms for use in clinical settings, derive new biological and medical insights and to improve our understanding of the factors underlying health and disease.
Nutrition
Key studies, courses and research groups
Degree Programmes
- MRes in Biomedical Research: Data Science
- MSc Health Data Analytics and Machine Learning
- MSc in Bioinformatics and Theoretical Systems Biology
Short Courses
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Section leadership
Head of Bioinformatics - Professor Timothy Ebbels
Professor Ebbels is a Professor of Biomedical Data Science and his research interests lie at the interface between two broad areas:
- multivariate data analysis
- post-genomic technologies
More specifically, on the computational side these include, machine learning, bioinformatics, chemometrics, and multivariate statistics, and on the experimental side, the fields of genomics, transcriptomics and metabolomics.
Bioinformatics events
All EventsResearch group leads
Dr Elsa Angelini
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Dr Elsa Angelini
ITMAT Data Science group
Professor Timothy Ebbels
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Professor Timothy Ebbels
Bioinformatics
Professor Robert Glen
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Professor Robert Glen
Computational Medicine
Dr Joram Posma
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Dr Joram Posma
Cancer Informatics