Dr. Tran Chau My Thanh, a dedicated researcher at Duy Tan University, Vietnam 🇻🇳, holds a medical degree and Ph.D. from Hue University of Medicine and Pharmacy 🎓. Her work bridges the gap between clinical medicine and molecular biology 🧬. With a strong passion for translational research, she focuses on using bioinformatics and genomic tools for early diagnosis and targeted therapy development for diseases like cancer, diabetes, and cardiovascular disorders 💉. Through CRISPR/Cas9 and RNA networks, she aims to revolutionize patient-specific treatment pathways 🚀. Her extensive lab experience, scholarly publications, and ongoing innovations make her a promising leader in biomedical science 🏅.
Profile
Education 🎓
Dr. Thanh earned her Medical Degree (M.D.) from Hue University of Medicine and Pharmacy 🏥 and went on to complete her Doctorate (Ph.D.) in the same prestigious institution 🎓. Her education was deeply rooted in both clinical and research training, equipping her with a comprehensive understanding of human health and disease 🧠. Throughout her academic journey, she focused on genomics, molecular medicine, and biotechnology 🔬. The rigorous curriculum and hands-on exposure in advanced labs trained her in modern diagnostic tools and therapeutic innovations ⚙️. She also mastered computational biology and molecular interactions, forming a solid foundation for her groundbreaking work in RNA regulation and gene editing technologies such as CRISPR/Cas9 🧪.
Experience 👨🏫
Dr. Thanh brings rich experience as a medical doctor and academic at Duy Tan University 🏫. Her research career spans multiple roles in molecular diagnostics, bioinformatics, and therapeutic innovation 🧬. She has led studies on disease biomarkers, participated in international collaborations 🌐, and worked extensively with cell lines, recombinant DNA, and next-gen sequencing data 🔍. Her proficiency in wet lab and dry lab environments empowers her to integrate experimental biology with computational modeling 🧫💻. Alongside mentoring students and publishing SCI-indexed research, she contributes to translational medicine by connecting bench science to bedside applications, helping advance precision medicine for critical illnesses 💡.
Awards & Recognitions 🏅
Dr. Thanh is a nominee for the Young Scientist Award by the International Cognitive Scientist Awards 🧠🏆. Her impactful work on circular RNAs, miRNAs, and disease biomarker networks has garnered international recognition 🌍. She’s been acknowledged in high-impact journals for discoveries related to coronary heart disease and cancer diagnostics 📖. Her scholarly articles are indexed in SCI and Scopus, and she continues to influence the biomedical community through conference presentations, peer reviews, and academic collaborations 🤝. As a rising figure in molecular biology, her research promises transformative outcomes for early disease detection and targeted therapies 🧬✨.
Research Interests 🔬
Dr. Thanh’s research explores circRNA/miRNA/mRNA interactions, protein-protein networks, and gene function analysis 🧬🧠. She is driven by the quest to discover novel biomarkers for early diagnosis of complex diseases such as cancer, stroke, and diabetes 💊. Her focus includes CRISPR/Cas9 gene editing, molecular docking, and simulations for drug discovery and target validation 💻🧪. She also builds interaction networks to map LncRNA/CircRNA/miRNA/gene/protein-drug relationships, contributing to personalized medicine approaches 🎯. Through bioinformatics, she decodes gene expression dynamics and immune infiltrations to enable efficient diagnostics and therapeutics 💡. Her ultimate goal is to bridge computational biology with translational research for global health improvement 🌐💚.
1. Hsa_circRNA_0000284 acts as a ceRNA to participate in coronary heart disease progression
by sponging miRNA-338-3p via regulating the expression of ETS1
2. Identification of hsa_circ_0001445 of a novel circRNA-miRNA-mRNA regulatory network as
potential biomarker for coronary heart disease
3. Potential diagnostic value of serum microRNAs for 19 cancer types: a meta-analysis of
bioinformatics data