Selected Projects

What follows are real projects, at a level that protects our clients – the questions we work on and the methods we apply. Most projects are under NDA. Roughly even split between academic groups and biotech clients. Several ran in close, ongoing contact with our clients’ wet-lab teams, computational findings shaping bench priorities as the work developed, not delivered cold at the end.

Protein Structure Modelling and Multi-Species Epitope Verification

Client: Biotech

Epitope identification and cross-species reactivity verification to directly inform an antibody development pipeline.

A biotech client required protein structure modelling to identify both linear and conformational epitopes in a target protein – and needed those epitopes verified for cross-species reactivity across a range spanning animal to human.

We modelled protein structures and systematically identified epitope candidates, distinguishing between linear regions accessible in the unfolded protein and conformational epitopes dependent on three-dimensional structure. Cross-species sequence and structural comparison then assessed how conserved each candidate was across the relevant species range, providing a confidence-ranked set of targets for experimental validation.

The analysis directly informed the client’s antibody development pipeline.

Preliminary Data and Grant Development for Group Leaders

Client: Academia

Publication-quality figures and computational feasibility work generated ahead of submission to strengthen grant applications.

Group leaders approached us with grant applications in preparation (ERC, BBSRC, DFG) – proposals where the biological concept was clear, but the preliminary data needed to make them competitive was not yet in place.

We developed that data. For groups with existing datasets, we analysed and produced publication-quality figures ready for direct inclusion to their research grant. For concepts that needed testing before experimental work could be justified, we worked the question through computationally – establishing whether the idea held up with publicly available data before a sample was collected or a sequencer switched on.

The outcome in each case was a stronger application: figures that supported their hypothesis, a credible analytical plan and a clear account of what the proposed work would show.

Diagnostic Marker Discovery Across Pathogenic and Non-Pathogenic Species

Client: Biotech

Pangenome-level protein comparison to identify pathogen-specific epitopes with no off-target activity in beneficial species.

A biotech client needed to identify protein-level diagnostic markers that distinguish pathogenic species from closely related non-pathogenic ones – markers specific enough to bind in the target but with no off-target activity in beneficial species.

We assembled and compared pangenomes across multiple species, annotated gene content and called proteins across the full set. Cross-species protein comparison identified candidates unique to the pathogenic group. We then mapped linear epitopes – regions where antibodies could bind in the pathogen – and verified that equivalent regions in the non-pathogenic species were sufficiently divergent to avoid off-target binding.

The analysis delivered a shortlist of verified epitope candidates directly actionable for antibody development.

Pangenome Analysis and Prophage Annotation for Phage Engineering

Client: Biotech

Systematic prophage survey across bacterial species to establish the genomic foundation for a phage engineering programme.

A biotech client developing phage-based applications needed a systematic survey of prophage content across a set of bacterial species – identifying which phages were present, where they integrated and what their gene content revealed about engineering potential.

We built pangenomes across the target species, annotated prophage regions and characterised gene content and integration sites throughout. The work was carried out in close collaboration with the client’s wet-lab scientists, integrating computational findings directly with experimental priorities as the project developed.

The analysis provided the genomic foundation for the client’s phage engineering programme.

Metagenomic Taxonomy and Biosynthetic Potential of Unknown Species

Client: Academia

Taxonomic placement and biosynthetic gene cluster characterisation of environmentally derived organisms with no close database reference.

A research group working with environmentally derived samples needed to characterise organisms that resist conventional classification – species with no close reference in existing databases, recovered from contexts where standard taxonomic approaches break down.

We are developing and applying approaches to push taxonomic resolution as far as the data allows: placing these organisms as precisely as possible within the tree of life, characterising their genomic content and identifying biosynthetic gene clusters and metabolic pathways that point toward novel enzymatic or natural product potential.

The work sits at the boundary between environmental metagenomics and synthetic biology – using what can be resolved about an organism’s identity as the starting point for understanding what it might be made to do.

Cross-Host Transcriptome Analysis to Identify Virulence Factors

Client: Academia

Differential expression analysis across host environments to identify virulence factor candidates and shape experimental priorities.

A research group studying host-pathogen interactions needed to understand how a pathogen’s gene expression changes across different animal hosts – specifically, which virulence-associated genes are differentially expressed depending on the host environment.

We performed a cross-species transcriptome analysis, comparing expression profiles of the pathogen across multiple host contexts. Differential expression analysis identified virulence factor candidates whose activity varied systematically with host, providing a ranked set of targets for follow-on functional work.

The findings shaped the group’s experimental priorities for subsequent studies.

Tissue Microbiome Profiling Under Antimicrobial Treatment

Client: Academia / Biotech collaboration

Microbiome profiling across treated and untreated animals to characterise treatment-associated shifts and inform treatment design decisions.

A joint academic-biotech collaboration needed to determine whether antimicrobial treatment produced measurable shifts in the tissue microbiome of treated animals – and if so, which microbial populations were affected and in what direction.

We profiled tissue microbiomes across treated and untreated animals, characterising community composition, diversity and the relative abundance of specific microbial groups. The analysis identified treatment-associated shifts in microbiome structure and flagged microbial taxa whose abundance changed consistently with treatment, providing a biological basis for interpreting the treatment’s broader effects.

The results contributed directly to the collaboration’s decision-making on treatment design.