• 👋 Hi, I’m Daniel J. Gomez, a graduate student researcher at Stanford University School of Medicine and California State University, East Bay.
• 👀 I’m interested in biomedical translational research, genetics, genomics, bioinformatics, exercise immunology, computational/systems cancer biology, spatial proteomics, spatial transcriptomics, precision and evidence-based medicine.
• 🌱 I’m currently learning exercise immunology, computational cancer systems biology, and multimodal analysis as well as big data omics approaches.
• 💞️ I’m doing research, development, and analytics in basic science and translational biomedical research for multiple consortia MoTrPAC, HCA, HuBMAP, and HTAN.
• 📫 How to reach me sfdanielgomez@gmail.com
• 😄 Pronouns: he/him/his
• ⚡ Fun facts: I've authored several scientific peer-reviewed publications, and presented to global audiences.
• I won 1st, 2nd, and 3rd place in grappling/jiu-jitsu competitions, and played other sports including basketball, soccer, football, and volleyball.
• I've also did lighting design for over 20 productions across U.S. cities, universities in multiple states in the USA.
• I've played multiple musical instruments: piano, clarinet, saxophone, guitar, 2nd violin, made 1st violin, and played orchestra internationally.
• I've also stayed consistent in doing state-of-the-art academic biomedical research in six different medical schools and one veterinary medical college (Stanford Medicine, JABSOM, JHUSOM, UCSDSOM, UFCVM, DUCOM) and industry-level methods.
• I also love collaborating with other innovative academic institutions and companies!

My Academic profile is here for your viewing pleasure 🧭 🌎.

• 🗺️ My present graduate studies is in Molecular and Cellular Atlases, Spatially Resolved Technologies. Single-Cell RNA Sequencing, Digital Pathology, Deep Omics Profiling in Health and Disease, AI/ML Data Science and Cloud Computing in Precision Medicine, Biomedicine, Genetics and Genomics, Multiomics, Translational Medicine, Immunology, Pathogenomics and Computational Biology. Currently, I am doing my thesis research on creating multi-modal maps of exerkines in spatially resolved multiomics with preclinical model data and the human biomolecular atlas project spatial data, exercise and physical activity multiomics, interorgan communication, signal transduction networks, and building multiscale single-cell spatial profiles of interorgan crosstalk at single-cell resolution, near-single cell super-resolution, and connecting cell-cell interactions with ligand-receptor interaction cascades and functions inside the cell that display the effect of exerkines measured in health, resilience, and disease.

You can access and read my papers on Google Scholar or

Research:

• Precision Medicine
• Exerkines and Exercise
• Mechanisms that underlie the benefits of exercise (exercise science research)
• Exercise Genetics, Biochemistry, Molecular Biology, and Physiology
• Precision Medicine to Network Medicine
• Computational biology and whole-organism models
• Spatial Multi-Omics and Multiplex Imaging
• Histology and histopathology (Pathogenetics and pathogenomics)
• Single-cell sequencing (sc/snATACseq, sc/snRNAseq, CITE-seq, etc)
• Developing analytical tools to harness both high-dimensional single-cell phenotype data and spatial info
• Spatial analysis of tissue architecture, neighborhood coordination and proximity analysis (cellular niches/areas)
• Annotating spatially resolved single-cell data by spatial cell learning
• Multi-omics multi-tissue molecular mapping (Tissue- and Organism-Wide Multi-omics)
• Molecular Bioengineering, Nanotechnology, Nanomedicine, and Cell and Gene Therapy
• Cellular Physiology Contextualization

Technique Interests:

• Genomics, Transcriptomics, Proteomics, Metabolomics (multiomics)
• Single-cell Imaging
• Structural Variations and Predictions
• Systems Biology and Applications
• Biological Modeling and Evaluation, Drug Development
• Data visualization, Data analytics, Clinical Data Mining
• Biological and Disease Modeling (AI/ML/DL)
• Imaging and Microscopy (histology, whole slide imaging, multiplexing)

• Data Science and Cloud Computing of Precision Medicine
• Cloud computing
• Bioinformatics
• AI/ML
• Supervised Learning
• Unsupervised Learning
• Neural Networks
• Deep Learning
• Large Language Models (LLMs)
• Data Analysis and Data Visualization
• Algorithm Development
• Computational Biology
• Statistical analysis and computing
• Functional assay development and experimental design
• Sequence analysis
• DNA isolation
• Phylogenetics
• Tissue (in situ) experiments (H&E, immunohistochemistry, in situ hybridization)
• Reinforcement Learning
• Processing large data sets
• Big Data and Omics
• Single-cell multiomics and Spatial omics research
• Digital pathology

• Exercising (resistance training, cardiovascular exercise (running, etc.), functional strength and circuit training)
• Hiking, Cycling, and Climbing
• Reading, Listening to Audiobooks and Podcasts
• Music and Movies