Focused scientific service
Bioinformatics & Computational Biology
Bioinformatics and computational analysis supporting genomics, transcriptomics and data-driven biological research, with emphasis on experimental alignment, analytical rigour and biological interpretation.
Request a Quote
From data to biological insight
Computational analysis aligned with the research question
Bioinformatics support covers both internally generated laboratory data and externally produced datasets from academic, clinical or public sources.
Projects are scoped around the data type, analytical objective and intended biological interpretation, and may combine genomics and transcriptomics analysis, statistics, visualisation and computational support for experimental and preclinical research.
Specific pipelines, tools and deliverables are reviewed during technical scoping; no single workflow is assumed to suit every dataset.
Bioinformatics capability groups
Support across the analysis lifecycle
Capability selection depends on the data type, research question and the level of analytical support required.
Genomics Analysis
Analysis of DNA-based datasets supporting variant detection, annotation and genomic characterisation.
- Variant calling and annotation
- SNP and small-variant analysis
- Comparative genomics
Transcriptomics & Gene Expression
RNA-based data analysis supporting gene-expression profiling and pathway interpretation.
- RNA-seq data analysis
- Differential gene expression
- Pathway and enrichment analysis
Statistical Analysis & Visualisation
Statistical modelling and visualisation supporting interpretation of experimental and biological datasets.
- Statistical testing and modelling
- Graphical data representation
- Reproducible analysis workflows
Computational Biology
Computational approaches supporting biological modelling, data integration and hypothesis generation.
- Biological data integration
- Computational modelling
- In silico exploratory analysis
Support for Experimental Studies
Computational support aligned with laboratory and preclinical workflows.
- Experimental design support
- Integration with wet-lab results
- Coordinated reporting
Execution Model
Structured, reproducible and documented workflows designed for transparency and biological relevance.
- Clearly defined analytical objectives
- Reproducible, documented workflows
- Interpretation aligned with research context
Final tools, pipelines and deliverables depend on the dataset and project requirements and are confirmed during scoping.
How projects move forward
A practical five-step workflow
The process begins with the analytical goal and data type and defines scope, deliverables and reporting before analysis begins.
Initial enquiry
Share the project objectives, data type and research context.
Scientific scoping
Review analytical scope, feasibility and data requirements.
Analysis plan
Agree a customised analysis plan, deliverables and quotation.
Analysis
Proceed using the agreed, documented workflow.
Interpretation & reporting
Review results, biological interpretation and connected next steps.
Related routes
Connect this service with the wider project
Research & Laboratory Services
Use the main gateway when the project spans multiple laboratory or analytical disciplines.
Explore the gateway →Molecular Biology & qPCR
Generate molecular data with nucleic-acid, PCR and qPCR workflows.
View the service route →Preclinical Research
Integrate computational analysis with in vitro and in vivo study data.
View the service route →Bioinformatics Training
Build in-house skills through the Bioinformatics & Computational Sciences Diploma.
View the diploma →Discuss your data and analysis goals
Share your objectives, data type and research context so the appropriate analysis plan and quotation can be prepared.