Blueprints of Life: The Basics of Genes and Genetic Testing

Genetic Glitches: When the Code Misfires

From Code to Cure: Engineering Precision Treatments from Genetic Data

Biography:

Émile Moura, MS, CGC, is a certified genetic counselor in the Department of Neurology at UTHealth Houston. She provides genetic counseling to both pediatric and adult patients with epilepsy and neurodevelopmental disorders. In addition to her clinical work, Émile is involved in genetic variant interpretation and contributes to research aimed at advancing the understanding of genetic epilepsies.

Ludovica Montanucci, PhD, is an Assistant Professor at UTHealth Houston. She holds a PhD in Physics from the University of Bologna (Italy), where she developed a strong interest in complex adaptive systems and machine learning. Her research integrates computational modeling and data-driven approaches to study biological systems at the molecular and cellular levels, with applications ranging from protein folding and stability to the prediction of structural and functional properties of proteins from sequence data, as well as the modeling of biomolecular network evolution and the interpretation of genomic variation. At UTHealth, her work focuses on developing machine learning methods to predict the impact of genetic variants in monogenic neurodevelopmental disorders, linking molecular alterations to protein function and clinical phenotypes.

Jessica C. Lal, PhD is a CPRIT TRIUMPH Postdoctoral Fellow at MD Anderson Cancer Center, where she works at the intersection of cancer biology, data science, and precision medicine. She earned her PhD in Molecular Medicine from the Cleveland Clinic, where she developed expertise in translational genomics and clinical biomarker discovery related to cancer therapy adverse events. Dr. Lal’s research focuses on using multi-omic data—integrating genomics, transcriptomics, and clinical information—to better understand how tumors evolve and interact with the immune system. Her current work applies cutting-edge bioinformatics tools to study how genetic changes in colorectal cancer shape the tumor microenvironment, with the goal of developing more personalized and effective treatment strategies.

Suyeon Kim is a Postdoctoral Research Fellow at UTHealth Houston. She recently earned her PhD in Biomedical Informatics from the University of Nebraska at Omaha, where her research focused on developing graph-based data models and computational pipelines to integrate multi-omics and microbiome data for the identification of clinically relevant microbial biomarkers. Her broader research interests include multi-omics integration, microbial ecology, high-performance computing, and translational genomics.

Address:United States