Research group

BiOmics

Bar coded DNA sample

Technological advances have allowed scientists to gather large amounts of data about a vast array of species, organisms and single cells. Our researchers are using mathematical modelling, machine learning and other algorithms to extract information and patterns from large data sets to further our understanding of disease.

About

Contemporary scientific research benefits from rapid technological developments that enable the characterisation and quantification of biological molecules at unprecedented scale. Scientists can generate vast data that provide insight into the complex interplay of molecules within organisms. Interrogation and interpretation of these data inform the structure, function and interaction of molecules over time. 

We use ‘Omic technologies comprehensively to evaluate DNA (genomics), RNA (transcriptomics) and proteins (proteomics). We study small molecules using metabolomics. Microorganisms are investigated in a targeted manner using microbiomics or more broadly to characterise mixed samples using metagenomics.

At the University of Southampton, we generate vast datasets using these approaches across a wide range of environments and species. We work closely with NHS partners to use these capabilities to understand human disease and inform its clinical management. We bring together medical and biological scientists with mathematicians, computer and data scientists to develop and apply methods that exploit these data to their fullest potential.

From analysing patient genomes, to carrying out metagenomic analysis of water samples to using mass spectrometry metabolic profiling techniques, our scientists are studying the unique processes that take place within cells that can lead to disease or poor health outcomes in humans and help track changes in the environment.   

We are using data to answer clinical questions in areas such as cancer, autoimmune and respiratory diseases with the help of clinical colleagues we are translating our findings into novel techniques for clinicians to treat their patients, make predictions about prognosis and drug responsiveness.

Our researchers collaborate with partners at:

People, projects and publications

People

Professor Mark Sullivan

Associate Dean-Research

Research interests

  • Supernovae
  • Time domain astronomy
  • Cosmology

Accepting applications from PhD students

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Dr Markus Brede

Associate Professor
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Professor Markus Heller

Professor of Biomechanics
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Professor Martin Browne

Professor of Applied Biomaterials
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Professor Martin Feelisch

Prof of Exp Med & Int Biol

Research interests

  • Role of Nutrition and Exercise in Health & Resilience
  • Origin-of-Life Chemistry and Evolution
  • Stress Signaling & Redox Regulation

Accepting applications from PhD students

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Professor Martin Kunc

Professor in Business Analytics

Research interests

  • Business Analytics
  • Strategic Modelling
  • Scenario planning
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Professor Martin Solan

Professor of Marine Ecology

Research interests

  • Biodiversity ecosystem function bioturbation benthic ecology

Accepting applications from PhD students

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Dr Martin Stolz

Lecturer-Biomedical + Orth. Tribology
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Dr Martin Warner PhD

Associate Professor
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Professor Martyn Hill

Professor of Electromechanical Systems
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We are at a very exciting time in Life Science Research. The potential for novel discovery using ‘omics technologies combined with the computer science methodologies is immense.
Professor of Genomics

Related research institutes, centres and groups

Related research institutes, centres and groups

Contact us

Contact us

Contact the Institute for Life Sciences team by emailing: