Genomics & bioinformatics
Analysis of sequencing data, variant interpretation and population reference data, building on GenoFlow, our genomic analysis platform.
Research areas
We are starting with three areas where we already have platforms and experience, and will add others as collaborations develop.
Computational chemistry
Molecular modelling, virtual screening pipelines and machine learning on chemical and materials data.
AI for science
Applying machine learning to research datasets, with reproducible training, evaluation and documentation.
What we provide
Each collaboration gets the engineering it needs. We can also write the technical sections, budgets and data management plans for joint funding applications.
- Compute
Computing and data infrastructure
Cloud or on-premise environments sized for the project, with data kept where ethics approvals and regulations require.
- Pipelines
Analysis pipelines
Versioned, reproducible workflows that other researchers can rerun and check.
- Software
Research software
Tools, dashboards and APIs built for the project, released as open source where possible.
- Security
Data protection
Access control, encryption and audit trails for sensitive data such as patient or genomic records.
How a collaboration works
Researchers keep ownership of their questions and findings. We are responsible for the systems behind the work.
- 01
Question
You bring the research question, the data involved and the constraints.
- 02
Plan
We agree scope, data handling, ownership and publication, and apply for funding together where needed.
- 03
Build
We set up the infrastructure and pipelines and develop the software.
- 04
Run
The analysis runs, and we support and adjust it as the research develops.
- 05
Share
Researchers publish the findings; code and methods are shared openly where possible.