Computational Biology Consulting
Turning omics data into
drug discovery insights
Two decades in computational biology, eight of them in pharma, and now building AI tools that turn data and knowledge into evidence-grounded insights so teams make drug-discovery decisions faster.
Across the pipeline and in both directions: from discovery to the clinic, and back. For teams from preclinical biotechs to large pharma.
Multi-Omics Analysis
Integrated analyses of RNA-seq, single-cell, spatial transcriptomics, and proteomics data that connect molecular signals to biology.
AI for Data Analysis
Practical LLM tooling for biomedical data analysis, including literature mining, evidence extraction, and analytical code review.
Pharma-Ready
Deep experience at Bristol Myers Squibb, Jackson Laboratory, and Princeton University.
Research & tools
Methods and software built at TensorOmics, in the open where I can.
Paper · Open source
ProteoEM
Protein abundance from single-molecule affinity traces, adapting RNA-seq's EM to proteomics.
Live
TheraRadar
Competitive intelligence for pharma and biotech: search any drug, company or target across approvals, trials and patents, with weekly briefs.
In development
TensorTarget
An AI co-scientist for drug-target discovery, being built to turn genetics and omics data into testable target hypotheses.
Where the work has been
Hands-on experience across the drug discovery pipeline, from target nomination to biomarker discovery to single-cell analysis.
Ready to accelerate your research?
Let's discuss how TensorOmics can support your next project.
Get in Touch