Jose Ramon Jeronimo Liñan
Bridging biology and computation to turn biological data into decisions
As a bioprocess engineer, I bring the biological understanding behind the data — along with laboratory and industrial experience — to my computational biology work
Get in touchBridge
Bioprocess engineering taught me to read biological systems under pressure — optimizing fermentation runs, designing controlled experiments, and translating batch data into process decisions. That training built a skill most computational pipelines lack: the ability to look at a statistical output and ask what it means for the organism, not just the model. I build workflows with that lens built in, so the results translate into actions, not just plots.
What I bring:
- Experimental design experience that catches data quality problems before they reach the pipeline
- The biological grounding to interpret computational outputs in context — not just report them
- Industrial and research exposure across fermentation, microbial systems, and omics
Projects
gempipe
Manually discovering where a metabolic pathway is broken is painful. Gempipe provides the reactions that are causing the model to fail, shortening the discovery time from hours of manual search to minutes of automatic computing
Quick overview ↓Skills
Python · Data
pandas numpy scipy matplotlib seabornPython · ML & Bio
scikit-learn cobrapy scanpy streamlitBash Tools
gapseq samtools bowtie2 fastqc fastpLanguages
- Python
- SQL
- VBA
Contact
Open to roles in computational biology, bioinformatics, and research.