Hello ✨ I am Daniel Gomez, an innovative 👨🔬 Molecular Biologist, Computational Biologist and Engineer 👨💻!
- 👋 Hi, I’m Daniel J. Gomez, a graduate researcher at Stanford University School of Medicine.
- 👀 I’m interested in genetics, genomics, bioinformatics, exercise immunology, computational/systems cancer biology, spatial immunotherapy, precision medicine, and evidence-based medicine.
- 🌱 I’m currently learning computational cancer genetics, exercise immunology, and multimodal spatial and big data omics approaches.
- 💞️ I’m doing research and development, and analytics in basic and translational research for multiple consortia MoTrPAC, HuBMAP, HTAN, PsychENCODE, and All of Us Researchers.
- 📫 How to reach me sfdanielgomez@gmail.com
- 😄 Pronouns: he/him/his
- ⚡ Fun fact: I won 1st, 2nd, and 3rd place in grappling/jiu-jitsu competitions, played football, soccer, volleyball, played piano, clarinet, saxophone, guitar, 1st violin, 2nd violin, and did academic research in 6 different medical schools and 1 veterinary medical college (Stanford Medicine, JABSOM, JHUSOM, UCSDSOM, DUCOM, UFCVM).
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
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 and Proteomics, Metabolomics (multiomics), Structural Variations and Predictions
- Systems Biology and Applications
- Biological Modeling and Evaluation, Drug Development
- Data visualization, Data analysis, Data mining
- Biological and Disease Modeling (AI/ML/DL)
- Molecular neuroimmune-pathology, psychoneuroimmunology (PNI), neuroimmunopharmacology (NIP)
- Neurotherapeutics and Nanotherapeutics discovery
- Morphology and imaging (histology, whole slide imaging, multiplexing)
LinkedIn: /in/danieljgomez1/
- 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, functional strength and circuit training)
- Hiking, Cycling, and Climbing
- Reading, Listening to Audiobooks and Podcasts
- Music and Movies