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- A multi-pronged approach to targeting myeloproliferative neoplasms
- A new paradigm of machine learning-based structural variant detection
- A whole lot of junk or a treasure trove of discovery?
- Advanced imaging interrogation of pathogen induced NETosis
- Analysing the metabolic interactions in brain cancer
- Atopic dermatitis causes and treatments
- Boosting the efficacy of immunotherapy in lung cancer
- Building a cell history recorder using synthetic biology for longitudinal patient monitoring
- Characterisation of malaria parasite proteins exported into infected liver cells
- Deciphering the heterogeneity of the tissue microenvironment by multiplexed 3D imaging
- Defining the mechanisms of thymic involution and regeneration
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- Doublecortin-like kinases, drug targets in cancer and neurological disorders
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- Epigenetics – genome wide multiplexed single-cell CUT&Tag assay development
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- Finding treatments for chromatin disorders of intellectual disability
- Functional epigenomics in human B cells
- How do nutrition interventions and interruption of malaria infection influence development of immunity in sub-Saharan African children?
- Human lung protective immunity to tuberculosis
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- Integrative analysis of single cell RNAseq and ATAC-seq data
- Interaction with Toxoplasma parasites and the brain
- Interactions between tumour cells and their microenvironment in non-small cell lung cancer
- Investigation of a novel cell death protein
- Malaria: going bananas for sex
- Mapping spatial variation in gene and transcript expression across tissues
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- Role of glycosylation in malaria parasite infection of liver cells, red blood cells and mosquitoes
- Screening for novel genetic causes of primary immunodeficiency
- Single-cell ATAC CRISPR screening – Illuminate chromatin accessibility changes in genome wide CRISPR screens
- Spatial single-cell CRISPR screening – All in one screen: Where? Who? What?
- Statistical analysis of single-cell multi-omics data
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- Using combination immunotherapy to tackle heterogeneous brain tumours
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- Using structural biology to understand programmed cell death
- Validation and application of serological markers of previous exposure to malaria
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Bioinformatics

Bioinformatics combines mathematics, statistics and computer science to solve complex biological problems.
Our bioinformatics research is revealing how molecules and cells normally function, and what changes occur in disease.
Bioinformatics research at the Institute
Our bioinformaticians are:
- Revealing the changes in molecules and cells that cause disease.
- Developing new methods to analyse complex experimental data, to provide new insights into health and disease.
- Identifying new avenues for treatments that target the molecules involved in disease.
Bioinformatics research is integrated within many other fields of our research in particular:
What is bioinformatics?
Bioinformatics uses mathematics, statistics and computer science to analyse complex biological systems.
A single cell contains thousands of molecules that are essential to the healthy functioning and development of the cell. Changes in these molecules can influence how cells behave. Certain changes within cells underpin disease formation.
Current medical research technologies can generate vast amounts of complex data, for example by simultaneously analysing the intricate sequence of the three billion DNA bases in the human genome.
Bioinformatics develops new ways to analyse this data, to understand more fully what is occurring in complex biological systems.
Bioinformatics analyses give researchers new insights into how molecules behave within cells, and how cells interact or change in disease.
From small molecules to big data
To study the role of different molecules in cells, and how changes cause disease, our researchers use a range of experimental techniques. Their aims include:
- Revealing and analysing the genome of diseased cells or infectious agents to understand how they cause disease, and how they might be treated.
- Uncovering the changes that convert a healthy cell into a diseased cell.
- Discovering genetic variants shared within families or populations that confer susceptibility to a particular disease.
- Simultaneously measuring variations in genes being switched on or off (gene expression), and aligning this with other changes within cells or tissues.
- Detecting how a treatment influences the behaviour of cells.
The experiments that measure these can generate huge amounts of data. Our bioinformatics researchers develop appropriate methods that enable the in-depth analysis and interpretation of these data.
From big data to new treatments
Bioinformatics analyses can provide new insights into the roles of particular molecules within cells, and how these molecules vary between people. This is uncovering the molecular causes of many diseases. In some cases, bioinformatics research can also pinpoint new strategies for diagnosing or treating diseases.
Bioinformatics is an important aspect of personalised medicine, which matches individual patients with the best treatment for their disease.
Developing new bioinformatics techniques
Bioinformatics research relies heavily on computational and statistical strategies to analyse and interpret huge data sets. Many of our bioinformatics researchers have been trained in mathematics, statistics and computer science. This allows them to develop new ways to address complex research problems presented through their collaborations with other researchers.
Researchers:
A joint effort by breast cancer researchers and bioinformaticians has provided new insights into the molecular changes that drive breast development.
Bioinformaticians identify the first evidence of genes involved in a currently incurable degenerative eye disease.
Institute researchers have contributed to a decades-long global effort that has revealed two new gene mutations that cause a rare type of epilepsy.