Biomedical, University of Texas at San Antonio, United States
Dr. Mario A. Flores is an Assistant Professor at the University of Texas at San Antonio with a joint appointment in Electrical and Computer Engineering (ECE) and Biomedical Engineering (BME). His research focuses on developing AI models for disease phenotype prediction, biomarker identification, and generating explainable mechanisms of disease progression. Dr. Flores has pioneered several genomics and AI-based tools integrating spatial transcriptomics and Electronic Health Records (EHR) to characterize tumor microenvironments. 💻🔬
Publication Profile
ORCID
Education:
🎓 B.S. in Electronics Engineering (Instrumentation) – Metropolitan Autonomous University, 2002. M.S. in Applied Mathematics – University of Texas at San Antonio, 2010. Ph.D. in Electrical Engineering (Computational Biology) – University of Texas at San Antonio, 2015
Experience:
Dr. Flores is an Assistant Professor at the University of Texas at San Antonio since 2020. He has previously held roles as a Postdoctoral Fellow at the National Institutes of Health (NIH) and as a Research Associate at the Greehey Children’s Cancer Research Institute. His expertise spans computational biology, bioinformatics, AI, and deep learning. He has contributed significantly to spatial biology and immuno-oncology, tackling diseases using innovative AI techniques. 🧬🤖
Research Focus:
Dr. Flores’ research delves into AI-driven disease modeling, integrating single-cell RNAseq, EHR, and RNA FISH imaging to study tumor microenvironments. His lab develops tools that predict disease gene dependence and identify dysregulated regulatory elements during disease progression. His ongoing work integrates AI with spatially resolved transcriptomics to study cancer and other complex diseases. 🔍🧠
Awards and Honors:
🏅 NIH Functional Peripheral and Central Vagal Neural Circuits Grant (PI), 2023-2025. Artificial Intelligence/Machine Learning Consortium Hub Specific Pilot Grant (PI), 2023-2025. Keystone Symposia Investigator Travel Award, June 2023
Publications Top Notes:
New tools for spatial biology transcriptomics & proteomics in immuno-oncology – Immuno-Oncology Insights (2023) DOI: 10.18609/ioi.2023.005
Cited by 5 articles.
Looking at the TMEs from the Spatial Transcriptomics Perspective – Advances in Cancer Research and Clinical Imaging (2022)
Cited by 8 articles.
Poster: The Tumor microenvironment of NSCLC – Keystone Symposia (June 2023)
Presented at Keystone Symposia on Single Cell Biology.