Omics for prediction and prognosis

Using molecular data to predict who will get a disease and how it will progress

Theme Translational data science

Using molecular data to predict who will get a disease and how it will progress

In this workstream we use large, complex molecular (‘omics’) datasets to identify biomarkers to predict who will get a disease and how it will progress.

We use machine learning to identify, optimise and validate these molecular biomarkers. We then combine them with data from health records, cohort studies and trials to develop disease prediction tools for use in a range of settings.

Our biomarker identification work will support other NIHR Bristol BRC themes, including respiratory and mental health.

View all research projects

Great Western Secure Data Environment

NHS England are developing and deploying a national secure data environment for research. A secure…

Theme Translational data science

Workstream Clinical informatics platforms

Preventing cardiovascular events in stroke patients

Having a stroke means you are more likely to experience a subsequent cardiovascular event. Cardiovascular…

Theme Translational data science

Workstream Genetic evidence to prioritise intervention

Exploring how obesity influences cancer survival

Evidence from different studies suggests that obesity or body mass index (BMI) might play a…

Theme Translational data science

Workstream Genetic evidence to prioritise intervention

Using biomarkers and machine learning to predict antidepressant resistance

Around half of patients with depression don’t improve after taking antidepressants. Clinicians need to…

Theme Translational data science

Workstream Omics for prediction and prognosis

Can DNA methylation biomarkers predict whether pleural effusion is caused by cancer?

Pleural effusion, where fluid builds up in the cavity around the lungs, can develop…

Theme Translational data science

Workstream Omics for prediction and prognosis

Using DNA methylation biomarkers to understand Parkinson’s disease severity and progression

The Biogen Tel Aviv Parkinson Project (BeatPD) looks in-depth at clinical and genetic information…

Theme Translational data science

Workstream Omics for prediction and prognosis

Biomarkers for screening and diagnosing lung cancer

In the UK, only 15 per cent of people diagnosed with lung cancer will still…

Theme Translational data science

Workstream Omics for prediction and prognosis

Creating the infrastructure to enable translational data analysis at scale

Our priority is to create the data infrastructure to enable analysis of linked administrative and…

Theme Translational data science

Workstreams Clinical informatics platforms Large, complex datasets

Data driven approaches to drug target prioritisation

Despite more money going towards developing drugs, the success rate of getting new drugs to…

Theme Translational data science

Workstream Genetic evidence to prioritise intervention