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Daniel J. Gomez
I am daniel gomez , I'm conducting independent or collaborative research and developing impactful innovations that address challenges across multiple research initatives (MoTrPAC, HuBMAP, Human Cell Atlas, PsychENCODE, Space Omics), projects, or diseases and conditions, building generative solutions in disease, genetics, exercise immunology, pregnancy, maternal and children's health, astroimmunology, digital biology, multi-omics, bioinformatics, generative models, LLMs, and foundational models, AIVCs, and observational and experimental methods in novel spatial omics, single-cell genomics, translational science, has the ability to communicate my findings in physical activity signaling exercise medicine pathways, immunotherapy, personalized medicine, and map organs that discover novel exerkines.
My work recently won an award for "Multiscale System Modeling and Cross-Organ Modeling" won Most Innovative Project Award in the Whole Person Physiome Hackathon 2026.
I'm a scientist in the Snyder Lab at Stanford University School of Medicine Department of Genetics doing innovative biological science research and testing, learning, generating hypothesis, implementing single-cell technologies in molecular and cellular science. I completed requirements for a M.S. in Biological Sciences at the California State University, East Bay.
I got a certification in the Fundamentals of Data Science in Precision Medicine and Cloud Computing at Stanford University School of Medicine, and completed my second certification in Fundamentals of AI/ML in Precision Medicine at Stanford Data Ocean, Stanford Deep Data Research Center. Previously, I completed a structural biology course on how to use Synchrotron radiation and determine macromolecular structures and macromolecular crystallography at Stanford-SLAC RapiData 2023 at SSRL in addition to earning a Cybersecurity for Lab Users certificate from CS 100 at SLAC National Accelerator Laboratory. I conduct RNA and protein engineering design experiments that are able to inverse design generate sequences, structures, and biomolecules from RNA to protein and back to RNA, I also work with several DNA Language Models (DLMs), Genomics Language Models (gLMs), Codon Language Models (cLMs), Protein Language Models (pLMs), and single-cell Foundational Models (scFMs). I'm also working on my single cell multi-omics model that has the capability to handle exerkine sequence generation and design.
I earned my Bachelor's of Science degree in Biology: Concentration in Cell and Molecular Biology from San Francisco State University. More information is available in my CV.
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Recent Events and Invited Talks
- [Nov. 2025] Snyder Lab 40 Year Alumni Reunion
- [Feb. 2025] Precision Medicine World Conference 2025
- [Nov. 2024] Stanford Spatial Biology Symposium, 10x Genomics, Stanford University
- [Nov. 2024] Gastric Cancer Summit 2024, National Cancer Institute, Stanford Medicine
- [Sep. 2024] Proteomics: From Genomics to Proteomics, Staford Healthcare Innovation Lab
- [Sep. 2024] Giotto Suite Workshop 2024, Boston University
- [Sep. 2024] Comprehensive Cancer Biology Training Program 2024, Stanford Cancer Institute, Stanford Medicine
- [Jun. 2024] Contextualizing Cellular Physiology Workshop, NIH NIDDK
- [May 2024] Genomics and Personalized Medicine Symposium, Stanford Genetics
- [Apr. 2024] Pediatric & Maternal Innovation Showcase 2024, Stanford Medicine Children’s Health
- [Mar. 2024] Metabolic Health Center Annual Symposium, Stanford Medicine
- [Aug. 2023] Spatial Biology Summit 2023, Stanford Pathology
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Research
Research Assistant, Genetics, Pathology, Immunology
My thesis research is on exerkines, exercise multiomics, health and disease, mechanobiology, astroimmunology, building 3D atlases with single-cell spatial maps at single-cell resolution with machine learning and sc/snRNAseq, spatial omics using computational next-generation tools. This novel research makes a big impact in multiple research communities (i.e., consortia):
Molecular Transducers of Physical Activity (MoTrPAC),
Genotype-Tissue Expression (GTEx) project,
Human Biomolecular Atlas Project (HuBMAP),
Human Tumor Atlas Network (HTAN),
Gut Cell Atlas,
Human Cell Atlas.
I'm interested in multiomics disciplines of medicine and biosciences, molecular biology, genetics, biomedical data science, computational biology, integrative multiomics, pathology, bioinformatics, biomedical data science/machine learning (AI/ML), single-cell and spatial biology, chemistry, structural biology, biophysics and immunophysics, tissue and organ architecture.
*Denotes co-first authorship
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