01
Bioinformatics pipeline development
Custom Snakemake or Nextflow workflows for RNA-seq, variant analysis, single-cell, pathway analysis, and multi-modal data processing.
AI-integrated bioinformatics and computational biology
Turn complex biological data into reproducible decisions.
Lattice BioFlow helps research teams, biotech companies, and health-data organisations design robust analysis workflows, interpret high-dimensional datasets, and build practical AI-enabled products around biology.
RNA-seq
Single-cell
Imaging analytics
Reproducible pipelines
AI workflow assistant
Client input
“We have RNA-seq + imaging data but no integrated story.”
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Lattice BioFlow engine
Study design audit → pipeline plan → biological interpretation map
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Deliverable
Reproducible report, figures, codebase, and decision-ready recommendations.
Built for teams working across discovery biology, translational research, and applied health data.
Academic labs
Biotech startups
Clinical research teams
Digital health builders
What we do
Service-oriented computational biology, not generic AI consultancy.
We combine biological domain knowledge, reproducible engineering, and practical AI tooling to move projects from scattered data to usable insight.
02
Data interpretation and reporting
Publication-grade biological interpretation, figure strategy, pathway narratives, statistical review, and executive summaries for non-technical teams.
03
AI-assisted research products
Internal AI tools for literature triage, experiment planning, data-QA, report generation, SOP support, and biological knowledge retrieval.
04
Imaging and quantitative biology analytics
Analysis pipelines for calcium imaging, microscopy, cell fluorescence quantification, signal extraction, segmentation, and phenotype scoring.
Productised services
Select the level of support you need.
Each product is scoped around a clear outcome. Start small, then scale into deeper technical delivery when the value is proven.
Fast start
Data & Pipeline Audit
For teams with messy datasets, uncertain analysis quality, or inherited code that needs technical review.
- Pipeline/code review
- Data quality risk map
- Prioritised action plan
Most useful
Reproducible Workflow Build
For research teams who need a clean, scalable pipeline that can be rerun, shared, and defended.
- Snakemake/Nextflow workflow
- Versioned environments
- Documentation and handover
Decision support
Biological Insight Report
For teams with processed data who need a coherent biological story, figures, and next-step interpretation.
- DE/pathway interpretation
- Figure-ready outputs
- Scientific narrative
AI enablement
AI Research Assistant Prototype
For teams wanting a controlled internal AI assistant around documents, SOPs, datasets, or literature workflows.
- Use-case discovery
- Prototype interface
- Governance recommendations
Representative work
Examples of problems we are built to solve.
Use this section to showcase completed case studies. The placeholders below are written to sound credible while leaving room for real project metrics.
Bulk RNA-seq pipeline for treatment-response analysis
Built a reproducible workflow from FASTQ QC through alignment, quantification, differential expression, GO/KEGG enrichment, and report-ready visualisation.
Calcium imaging feature extraction
Designed an automated analysis framework for trace normalisation, peak detection, stimulus-window metrics, and biological phenotype comparison.
AI-supported biological interpretation workflow
Structured omics outputs into testable biological hypotheses, pathway summaries, and decision-ready recommendations for experimental follow-up.
Solution Builder
Tell us the problem. We’ll map the right solution.
This form helps potential clients define their technical problem clearly. The preview generates a structured brief they can send to you.
How engagement works
A clear route from first conversation to useful output.
1. Diagnose
Clarify the biological question, data status, risks, constraints, and success criteria.
2. Design
Define the analytical route, tools, deliverables, timeline, and validation checks.
3. Build
Develop workflows, reports, figures, prototypes, or decision tools with reproducible documentation.
4. Transfer
Handover code, outputs, interpretation, and next-step recommendations in plain language.
Start a conversation
Have biological data but need a cleaner path to insight?
Send a short project description and we’ll help define the most practical next step.