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Hi, I'm Jonathan To 👋

Computational Biologist | Virologist | Proteomics Data Analyst

"Bridging high-throughput computational automation with wet-lab virology and drug discovery."

I am a dual-threat wet/dry lab researcher currently engineering the Python infrastructure for the BYU Mass Spectrometry Core and leading a functional screening team as a Research Virologist. My long-term focus is on Oncolytic Virotherapy, transitioning robust computational pipelines into rigorous, translational cancer research.


Research & Engineering Impact

  • Proteomics Infrastructure (BYU MS Core): Architected Python pipelines (Pandas/NumPy) for the Orbitrap Astral, scaling daily capacity from 15 to 100+ proteomes/day and reducing manual QC time by 85%.
  • Drug Discovery (Halia Therapeutics): Executed high-throughput small molecule screening, modeling 150+ high-precision IC-50 curves via GraphPad Prism to drive lead compound selection for neuroinflammatory inhibitors.
  • Virology Leadership (BYU): Led a 5-person functional screening team, executing high-volume plaque assays and generating high-titer viral libraries for downstream characterization.

Technical Stack

Domain Tools
Programming & AI Python (Pandas, NumPy, Scikit-learn), R, Git, AI Agents (Copilot, Manus)
Proteomics & Bioinfo FragPipe, DIA-NN, Proteome Discoverer, Basic RNAseq/Genomics pipelines
Wet Lab & Assays High-Throughput Screening (HTS), Flow Cytometry, ELISA, Phage Isolation, BSL-2 Cell Culture
Instrumentation Thermo Orbitrap Astral MS/MS, Cytoflex Flow Cytometer, Vanquish Neo UHPLC

Production Architecture

  • BYU-MS-Core-Automative-Proteomics-Tools (Live Production Code)
    • Overview: The active OS powering the BYU Mass Spectrometry Core.
    • Tech: Flask, NumPy, Pandas, Matplotlib.
    • Key Metrics: Enabled scaling to 100+ proteomes/day and ensured <20% CV validation across multi-lab studies.

📚 What I'm Currently Learning (2026 Focus)

  • Advanced R programming and Computational Genomics for clinical data
  • Molecular Virology and Tumor Immunology mechanisms
  • Refining foundational chemistry via UCSD Extension (Targeting PhD prerequisites)

Career Roadmap

I am pursuing a hybrid wet/dry lab trajectory designed to bridge the gap between bench science and data engineering.

  • Phase 0 (Current): Graduate BYU with BS in Microbiology (April 2026).
  • Phase 1 (2026-2027): Enter biotech industry to solidify wet-lab mastery while completing specific PhD chemistry prerequisites.
  • Phase 2 (2028-2029): Complete MS in Translational Bioinformatics (University of Utah) while working full-time.
  • Phase 3 (2030+): Enter a premier PhD program in Oncolytic Virotherapy/Cancer Biology with unmatched dual-threat expertise.

Goal: To combine industrial operational excellence with rigorous academic research training, ensuring therapies survive the transition from bench to bedside.


I'm looking to collaborate on

  • Translational Research: Projects bridging molecular virology, tumor immunology, and computational pipelines.
  • Open-Source Bio-Engineering: Developing bioinformatics tools and data architectures that accelerate wet-lab discovery.
  • High-Throughput Assays: Automating and scaling functional virology or drug screening workflows.

I'm looking for help with

  • Networking: Connecting with principal investigators and scientists focused on Oncolytic Virotherapy and Cancer Immunology.
  • Strategic PhD Admissions: Advice from researchers who successfully leveraged deep industry/biotech experience into top-tier PhD programs.
  • Translational Mentorship: Guidance from professionals navigating the bench-to-bedside pipeline.

Ask me about

  • Computational Architecture for Wet Labs: How to build automated MS/MS or screening pipelines using Python and AI agents.
  • High-Throughput Screening: Virological plaque assays, Flow Cytometry, and IC-50 modeling.
  • Non-Traditional Academic Paths: Leveraging biotech industry experience as a foundation for rigorous academic research.
  • Workflow Optimization: Balancing demanding full-time lab, engineering, and academic timelines.

Fun facts

  • I'm intentionally engineering a clinical-computational-research triple threat skill set to tackle complex oncological challenges.
  • I'm highly passionate about mentoring students from non-traditional backgrounds who want to break into computational biology.
  • Outside the lab and terminal, I enjoy cooking (usually ignoring the recipe), gaming, reading, and hiking!

Connect


"The best time to plant a tree was 20 years ago. The second-best time is now." - Chinese Proverb

I'm planting my tree now at age 26, and I'm excited to see it grow into a career advancing oncolytic virotherapy!

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