Computational Biology Consulting
Turning omics data into
drug discovery insights
Two decades in computational biology, eight of them in pharma — 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
RNA-seq, single-cell, spatial transcriptomics, proteomics — integrated analyses that connect molecular signals to biology.
AI for Data Analysis
Practical LLM tooling for biomedical data analysis — 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 we can.
Paper · Open source
ProteoEM
Protein abundance from single-molecule affinity traces, adapting RNA-seq's EM to proteomics.
In development
TensorTarget
An AI co-scientist for drug-target discovery, turning genetics and omics data into testable target hypotheses.
Where the work has been
From target nomination to biomarker discovery to single-cell analysis — hands-on experience across the drug discovery pipeline.
Ready to accelerate your research?
Let's discuss how TensorOmics can support your next project.
Get in Touch