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 Graham Roberts

Prof in Paed. Allergy & Resp. Medicine
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Dr Gregory Perry

Lecturer in Chemistry

Research interests

  • Organic Chemistry
  • Synthesis
  • Catalysis

Accepting applications from PhD students

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Dr Guido Maiello

Lecturer

Accepting applications from PhD students

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Dr Guy Denuault

Associate Professor

Research interests

  • Oxygen reactions in electrocatalysis
  • Theory and applications of nanoelectrodes, microelectrodes and nanostructured microelectrodes
  • Theory and applications of scanning electrochemical microscopy

Accepting applications from PhD students

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Professor Hans Michael Haitchi MD, MMed(INT), PhD, PD, MRCP(London), FHEA, PGcert

Professor

Research interests

  • Study of the asthma susceptibility gene A Disintegrin and Metalloprotease 33 (ADAM33) in early life and adult asthma and other chronic lung diseases.
  • Development of novel Anti-ADAM33 agents as potential disease modifying asthma therapy.
  • Multiomic study of the influence of the maternal environment (e.g. allergic asthma, obesity) during pregnancy on ADAM33 and other mediators and the early origin of lung disease in the Maternal Environment in Pregnancy (MEP) cohort.

Accepting applications from PhD students

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Dr Hansung Kim

Associate Professor

Research interests

  • 3D Computer Vision
  • Artificial intelligence (AI) for scene understanding
  • Audio-visual data processing

Accepting applications from PhD students

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Professor Hasan Arshad

Prof in Allergy & Clinical Immunology
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Dr Hayward Godwin

Associate Professor

Research interests

  • I have a number of research interests, and they are as follows:
  • - How we search for target(s) in the environment, particularly using visual searches.
  • - Eye movement behaviour, focusing on search tasks
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Dr Heather Armstrong

Lecturer in Sexual Health

Research interests

  • LGBTQ+ Sexual Health and Well-Being
  • Sexual Fluidity
  • Sexual Motivation

Accepting applications from PhD students

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Dr Helen Ogden

Associate Professor

Research interests

  • Flexible regression models
  • Models for longitudinal and clustered data
  • Models for count data

Accepting applications from PhD students

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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: