AI and machine learning

New tools for spatial biology transcriptomics & proteomics in immuno-oncology

Immuno-Oncology Insights 2023; 4(2), 33–38

DOI: 10.18609/ioi.2023.005

Published: 17 March
Mario Flores

Roisin McGuigan, Editor, Immuno–Oncology Insights, speaks to Mario Flores, Assistant Professor, University of Texas, San Antonio

Mario A Flores is an Assistant Professor of Electrical and Computer Engineering, joint appointment Biomedical Engineering, at the University of Texas at San Antonio. His research includes the development of novel deep learning and AI models that can perform cancer phenotype predictions, identify biomarkers, and generate explainable mechanisms. His lab has developed several genomics-based deep learning (DL)/AI tools for disease gene dependence prediction and identification of regulatory elements dysregulated during cancer progression. At present, his work is focused on integrating spatially resolved transcriptomics, single-cell RNAseq, and RNA fluorescence in situ hybridization (FISH) images to characterize the tumor microenvironment in liver models.