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Bioinformatics and data science

Making sense of genomic and healthcare data to improve diagnosis, treatments, and lives of patients.

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World-leading bioinformatics, life-changing results

Our bioinformatics and data science team plays a crucial part in the analysis of patients’ genomes.

At the forefront of the genomics industry, our teams use high-performance cutting-edge computing tools, technologies, and techniques to find and interpret genetic variation in undiagnosed rare diseases and cancer patients, from newborns to adulthood.

>170K

genomes processed

3.8M

variants in the Clinical Variant Ark

8,100+

positive diagnoses for rare disease patients and families

20-55%

diagnostic rate depending on clinical indication

Areas of work

Bioinformatics at Genomics England includes a wide range of scientific and technological areas. Beyond genomic data, our bioinformaticians also work with other types of "omics" and clinical data.

Bioinformatics operations

Support end-to-end sample flow from submission to genome delivery. Work closely with the Genomic Laboratory Hubs (GLHs) and research cohorts to deliver interpreted results, monitor data exchanges, and manage queries.

Bioinformatics engineering

Develop high quality code and products to deliver meaningful results to clinical scientists in the NHS. Implement cutting edge bioinformatics technology in pipelines and tools using best practices in software engineering.

Genome analysis

Drive the development of cutting-edge genome analysis approaches for diverse clinical applications, enabling world-leading personalised healthcare for everyone.

Bioinformatics research services

Enable and support high quality research using the unique Genomics England datasets, and engage with academic researchers and pharma partners to accelerate scientific discovery to benefit patients.

Applied machine learning

Accelerate progress for patients and research partners through the application of machine learning and other advanced data analytics. This is done using different types of patient-derived datasets, such as multi-omics, free text, imaging and other types of clinical data.

Scientific curation

Impact the analysis of every patient’s genome by keeping knowledge of genes and variants associated with disease up to date through crowdsourcing and collaboration with disease experts world-wide.