Host Cell Lab Suite Practical tools for high-performance biotechnology
Herramientas
Emiliano Balderas Ramírez frente al Instituto de Biotecnología, UNAM

Emiliano Balderas Ramírez

PhD Candidate in Biochemical Sciences · IBt-UNAM
Bioengineer · Programmer · Community Leader

PhD Candidate
UNAM · IBt
Data Scientist Associate
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I am a Bioengineer and PhD Candidate in Biochemical Sciences at Instituto de Biotecnología, UNAM, working under Dr. Tonatiuh Ramírez. My work spans upstream bioprocessing with CHO, S. cerevisiae, and E. coli systems; molecular biology (mutant construction & plasmid assembly); and full-stack software development for scientific workflows.

The Host Cell Lab Suite was born from necessity — the repetitive, high-stakes calculations of a PhD routine where a single arithmetic error can cost days of culture work. What started as local Python scripts evolved through AI-assisted live coding into a collection of reliable, offline-ready tools designed to eliminate human error and ensure reproducibility across labs worldwide.

Beyond the bench, I served for 3+ years as Coordinator of the Mexican Bioimaging Workshops (MBW), a high-impact initiative funded by the Chan Zuckerberg Initiative (CZI), Leica, UNAM, and CONACYT. That experience shaped a core conviction: access to good tools is a scientific equity issue — and open source is the answer.

Upstream Bioprocessing
CHO · S. cerevisiae · E. coli
Molecular Biology
Data Science & Python
Metabolic Engineering
MBW · CZI Coordinator
Scientific Publishing

The reproducibility problem in everyday lab work

Every day, researchers worldwide perform the same calculations — cell splits, dilutions, growth rates, media preparation — by hand or in fragile spreadsheets. One transcription error can invalidate an experiment, or worse, go unnoticed and compromise downstream data.

Host Cell Lab Suite encodes the correct formulas once, tests them rigorously, and makes them available to any lab, anywhere, for free. Each tool was designed by someone who has made (and caught) those exact errors at the bench — and decided to fix the problem at the source.

Built with a Live Coding workflow and AI assistance, these tools evolved from quick Python scripts into polished, offline-ready PWAs. The goal remains the same: reduce human error in high-frequency tasks so that global data is reproducible, comparable, and trustworthy.

Bioengineering & Wet-Lab

Currently working with CHO cells (batch & fed-batch, shake flasks & stirred-tank bioreactors), designing process strategies to optimize producer cell lines for biotherapeutic quality and productivity — maximizing titer while controlling critical quality attributes. Also proficient in Saccharomyces cerevisiae metabolic engineering and Escherichia coli mutant construction and plasmid assembly.

Biological Models

Mammalian Cell Culture CHO cells
Yeast Culture Saccharomyces cerevisiae
Bacteria Culture Escherichia coli

Bioprocessing

Bioreactor Operation Optimization & process control
Scale-up Process transfer strategies
Purification Downstream processing

Molecular Biology

Targeted Genome Editing CRISPR-Cas9 · Cre-LoxP · HR
Plasmid Assembly Golden Gate · Gibson · Gap Repair

Additional

Metabolic Engineering
Flow Cytometry FlowJo · sweetspot analysis
Programming & Data Science

Transitioned from local Python scripts to full-stack web applications through AI-assisted live coding workflows. Fluent in scientific data analysis, statistical modeling, and building offline-ready PWA tools — with a focus on making complex bioprocess data accessible and reproducible.

Languages & Runtimes

Python numpy · pandas · scipy · requests
JavaScript ES6+ · async/await · Fetch API
SQL joins · aggregations · window functions

Data Science & Machine Learning

Data Analysis pandas · NumPy · SciPy · Jupyter
Data Visualization matplotlib · seaborn · Plotly
Machine Learning scikit-learn · statsmodels · cross-validation

Web Development

Frontend HTML5 · CSS3 · responsive design
PWA & Web Apps Service Workers · offline-first · Web APIs
Version Control Git · GitHub · collaborative dev

Tooling & Workflow

Jupyter Notebooks interactive analysis · reproducible research
AI-assisted Development live coding · prompt engineering
Doctor en Bioquímica (PhD) En curso
Universidad Nacional Autónoma de México
Jul 2023 – May 2027
Instituto de Biotecnología — Departamento de Ingeniería Celular y Biocatálisis.
Maestría en Ciencias Bioquímicas (MSc) Titulado
Universidad Nacional Autónoma de México
Ago 2018 – Dic 2021
Calificación: 95/100 · Graduado con Honores · Beca CONACyT
  • Tesis: Conversión de xilosa a etanol en levaduras termotolerantes (Saccharomyces cerevisiae)
  • Laboratorio de Ingeniería de Rutas Metabólicas — grupo del Dr. Alfredo Martínez Jiménez
  • Cursos: Biología Molecular, Bioquímica, Ingeniería de Rutas Metabólicas, Perl para Biociencias
Ingeniería en Biotecnología (BSc) Titulado
Tecnológico de Monterrey
Ago 2012 – May 2017
Calificación: 91/100 · Beca completa SEDENA
  • Cursos: Diagnóstico Molecular I y II, Mejoramiento Genético, Procesos Biotecnológicos
  • Desarrollo profesional en Biología Molecular
Data Science Professional Track Completado
DataCamp
Jun 2020 – Jul 2023
Python, JavaScript y herramientas de Data Science. Incluye certificación Data Scientist Associate (Jul 2023).
Data Scientist Associate
DataCamp
Expedida: Jul 2023 · ID: DSA0012626645377

Acknowledgements

SECIHTI
Secretaría de Ciencia, Humanidades, Tecnología e Innovación — doctoral fellowship supporting this research.
PAPIIT IT201524
Programa de Apoyo a Proyectos de Investigación e Innovación Tecnológica, UNAM — project grant funding the experimental and computational work of this thesis.
Instituto de Biotecnología, UNAM
Host institution providing research infrastructure, laboratory facilities, and the academic environment in which this project was conceived and developed.