Data, statistics and population health
Statistics, bioinformatics, epidemiology and study delivery, for biomedical questions and well beyond them.
Our data practice brings together statisticians, epidemiologists and bioinformaticians from UCL, the University of Cambridge and Anglia Ruskin University. We work on clinical and laboratory data, large cohorts and health records, and datasets from outside biomedicine.
Statistics, Bioinformatics and Data Science
We turn complex data into reliable answers. Our statisticians support projects from experimental design and power calculations to analysis and interpretation, using methods that make findings robust and reproducible.
Our bioinformatics and data science work spans genomic, transcriptomic and proteomic data, large cohort and health-record datasets, and reproducible analysis pipelines. Many of these methods apply equally outside biomedicine.
Statistics
- Study design and sample size
- Descriptive and inferential analysis
- Regression and predictive modelling
- Longitudinal and survival analysis
Bioinformatics
- Sequence and variant analysis
- Gene and protein expression
- Genomic medicine datasets
- Open-source analysis pipelines
Data science
- Data cleaning, linkage and curation
- Reproducible workflows
- Visualisation and reporting
- Training for your team
Example projects
- 1
Sample-size calculations and a statistical analysis plan for a grant application or trial.
- 2
RNA-seq or variant analysis in a reproducible, documented pipeline, with publication-ready figures.
- 3
Cleaning, linking and analysing a large dataset, from health records to survey or operational data outside biomedicine.
Led by: Dr Timothy Hearn · Dr Sarah Assaad · Dr Shabina Hayat
Study Design and Implementation
Our epidemiologists specialise in the design, delivery and quality assurance of large cohort studies, strengthening the methods and operations behind population health research.
That includes SOPs, training and accreditation systems, data-quality monitoring and harmonised measures, so datasets are robust, comparable and relevant to policy.
Design
- Protocol development
- Sampling and participant selection
- Questionnaires and assessments
- Ethics and research governance
Delivery
- SOPs and fieldwork management
- Interviewer training and accreditation
- Data-quality monitoring
- Linkage with health records
Harmonisation
- Cross-national cognitive assessment (HCAP)
- Dementia outcome ascertainment
- Comparable, policy-relevant data
- Evaluation frameworks
Example projects
- 1
Designing a cohort study protocol, sampling frame and questionnaires.
- 2
Setting up fieldwork SOPs, interviewer training and data-quality monitoring.
- 3
Harmonising cognitive or health measures across countries so results can be compared.
Led by: Dr Shabina Hayat · Dr Sarah Assaad
Training and Networking
Basic, advanced and bespoke packages, delivered by Cambridge-trained epidemiologists with experience of ageing studies on four continents.
Interactive and hands-on, built on real examples from our facilitators' own research. Live sessions combine videos and slides, practical exercises and open discussion on a secure platform, with an individual account for each participant.
Example projects
- 1
A two-day course on study design and fieldwork quality for a research team.
- 2
A five-day hands-on course in data cleaning and analysis.
- 3
A bespoke networking visit connecting your team with UK experts in ageing research.
Led by: Dr Shabina Hayat · Dr Sarah Assaad
Training details and registrationTell us about your project
Your first consultation is free. We will propose an approach, a timeline and costs tailored to your goals.