Thanks for stopping by. Read below to learn more about myself and my background.

Daniel Gomez being chauffeured with an RdRp: NS5B


I am a molecular biomedical scientist and AI/ML Engineer focused on structural biology, collecting data and structure solution of particular molecular nanomachine (MNM), NS5B. Currently, I am studying structural molecular biology, biotechnology, and virophysics. My graduate thesis is on the structure-based discovery of this MNM and nanomotor. the replication complex (RC) in a replication organlle (RO) of the rare Flavivirus Human pegivirus-1 (HPgV-1) and solving structure and molecular biophysical questions surrounding the RNA-dependent RNA polymerase (RdRp).

I have been researching neuroimmunopharmacology in neurodegeneration (neurology & neurosurgery) since 2012, and in 2022 began researching neurosurgical oncology. This year, I began neuroendovascular surgery (NES) research on aneurysm subarchinoid hemorrhage (aSAH) healing, bioengineered drug eluting neuro-endovascular devices, robotics, and artificial intelligence. See our Planned paper in Bioengineering: AI in Surgery.

I have taken a liking to data-driven discoveries of AI in Neurosurgery, Computation and Neural Systems (CNS), Bioimage Informatics, and blending Computational Structural Biology (CSB) / Complex Biological Systems (CBS). My inventiveness advances SDS systems and standardizes SDS ontology. I advocate for interoperability, organizes data storage, and facilitates distribution/exchange. I plan on making data annotation more efficient and improving the quality of annotated data sets. These are some of the key initatives and current challenges of SDS.


MS, 2022-2024

California State University, East Bay (CSUEB)
University of California, San Francisco (UCSF)
Stanford Synchrotron Radiation Lightsource (SSRL)
SLAC National Acceleratory Laboratory, Stanford University

BS, 2022

San Francisco State University (SFSU)
Johns Hopkins University School of Medicine (JHUSOM)
John A. Burns School of Medicine (JABSOM)
University of Hawaii at Mānoa (UHM)


dry lab


  • Statistical Skills
  • Programming Skills
  • General Biology and Biomedical Knowledge
  • Knowledge of Genomics and Genetics to Multi-omics
  • Database Management
  • Data Mining and Machine Learning
  • Data Science and Engineering
  • AI applications, Large Language Models (LLM)
  • Decoding and Encoding

wet lab

molecular, tissue, and organ techniques

  • Basic Lab & Safety (GMP, BBP, IRB)
  • Phlebotomy (winged needle collection)
  • Cell viability assays
  • Funcational assay design
  • BBB in vitro models
  • Cell culture and co-cultures: Mammalian (primary and cell lines), prokaryotes (E. coli) and yeast (S. cerevisiae)
  • Growth Curves, Crystal Violet staining, MTT/MTS assay
  • DNA/RNA/Protein extraction
  • PCR, RT-qPCR, Fragment Analysis & Sequencing (NGS)
  • Gel Electrophoresis, Tapestation, Sonication
  • Tissue (in situ) experiments (IHC, ISH)
  • Surgical methods in toto "whole animal" to organ exisions, isolations, and cannulations ex vivo
  • Functinoal Genomics: Primer Design, Plasmid Miniprep
  • Site-Directed Mutagenesis (SDM)
  • Gibson Assembly