Computational AI & Bioinformatics
Our computational biology team runs the dry-lab half of every project: pipelines, statistics and AI models built to surface the signal that matters in your data, always interpreted by scientists, never handed over as a black box.
Alignment, quantification and QC, version-controlled end to end.
Combining genomics, transcriptomics and other layers into one coherent model.
Inference models to prioritize candidate biomarkers from complex datasets.
Predictive models built and validated on your biological question, not generic templates.
Linking omics results with clinical or phenotypic metadata for translational relevance.
Figures and dashboards built to be explored by your team, not just read once.
Every dataset moves through the same disciplined stack: processing, statistical analysis, biological interpretation and AI-assisted modeling, before it reaches a report.
Sequencing reads, arrays or clinical files, as delivered.
Alignment, quantification and QC on version-controlled pipelines.
Statistical testing, differential analysis, pattern discovery.
Pathway enrichment, biomarker prioritization, ML modeling.
Interactive dashboard plus written scientific interpretation.
Have a dataset that needs interpreting?