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

Dr Yihua Wang

Associate Professor

Research interests

  • Cell Signalling in Disease
  • Epithelial-Mesenchymal Crosstalk
  • Pulmonary Fibrosis

Accepting applications from PhD students

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Professor Ying Cheong

Professor of Reproductive Medicine
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Dr Ysobel Baker

Royal Society University Research Fellow

Research interests

  • DNA chemistry
  • Nucleic acid chemistry
  • Nucleic acid therapeutics

Accepting applications from PhD students

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Dr Yuning Zhang PhD

Lecturer in Psychology

Accepting applications from PhD students

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Dr Yury Bogdanov

Lecturer in Transgenic Technologies

Research interests

  • Tumour microenvironment
  • Neurotransmitters in Cancer
  • GABA and GABA receptors

Accepting applications from PhD students

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Dr Zehor Belkhatir

Lecturer

Research interests

  • Design of estimation and control techniques, with convergence guarantees, for finite and infinite-dimensional systems
  • Robust predictive modelling and analysis of high-dimensional data (e.g., network, time-series, imaging)
  • The cross-over between artificial intelligence and mathematics for interpretable and robust computational algorithmic designs

Accepting applications from PhD students

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Dr Zoe Saynor PhD, MSc, BSc (Hons), FHEA, RCEP

Associate Professor

Research interests

  • Physical activity and exercise in the prevention and treatment of long-term conditions
  • Clinical exercise testing and mechanism(s) of exercise limitation in long-term conditions
  • Paediatric exercise science

Accepting applications from PhD students

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Dr Zoë Walters

Associate Professor

Research interests

  • Target Prioritisation and Validation
  • Epigenetics and genomics
  • Cancer 

Accepting applications from PhD students

Connect with Zoë
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: