"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.

• 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.

• 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.

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

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.

• 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.

• 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.

• 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.

• 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!

• LinkedIn: linkedin.com/in/jonathanto99
• Focus: Oncolytic Virotherapy | Computational Biology | High-Throughput Drug Discovery

"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!