Prof Qinyu Ge, Southeast University, China
Prof. Qinyu Ge 🎓🔬 earned his Ph.D. in Biomedical Engineering from Southeast University in 2006. As a dedicated researcher at Southeast University, his work focuses on sample treatment and library preparation for high-throughput DNA sequencing 🧬, including spatial transcriptomics and whole-genome methylation studies. His expertise extends to designing DNA microarrays for cell-free nucleic acid, methylation, and DNA polymorphism detection 🧪. Prof. Ge has published extensively on topics like environmental DNA integrity, non-invasive embryo biomarkers, single-cell analysis, and deep learning in genomics 🤖📊, contributing significantly to biomedical research advancements globally 🌍.
Publication Profile
Scopus
Education
Prof. Qinyu Ge 🎓 is a distinguished scholar who earned his Ph.D. in Biomedical Engineering from Southeast University in 2006 🏫. Since then, he has devoted his academic career to the same institution, making remarkable contributions to biomedical research 🔬. His work has advanced the field through innovative studies and impactful publications 📚. Prof. Ge’s dedication to scientific excellence and education has played a key role in shaping the future of biomedical engineering 🌟. His commitment to research and mentoring young scholars continues to inspire the next generation of scientists 👩🔬👨🔬.
Research Interests
Prof. Qinyu Ge’s research focuses on innovative techniques in sample treatment and library preparation for high-throughput DNA sequencing. His work explores key areas such as spatial transcriptomics, providing insights into gene expression within tissue architecture 🧬, whole genome methylation studies to understand epigenetic modifications 🧪, and advanced DNA microarray design for precise genetic analysis 🔬. Through his contributions, Prof. Ge aims to enhance the accuracy and efficiency of genomic technologies, supporting breakthroughs in biomedical research and personalized medicine 🌍. His expertise continues to drive advancements in the rapidly evolving field of genomics and molecular biology.
Applications
Prof. Qinyu Ge is a leading expert in genomic technologies, making significant strides in cell-free nucleic acid analysis, methylation detection, and DNA polymorphism studies. 🧬🔬 His pioneering research has been instrumental in enhancing the accuracy and efficiency of genetic diagnostics, contributing to early disease detection and personalized medicine. 💡🧫 Through innovative approaches, Prof. Ge’s work bridges the gap between molecular biology and clinical applications, driving advancements in genomics and biotechnology. 🚀🌍 His dedication to scientific excellence continues to inspire breakthroughs, shaping the future of genetic research and healthcare. 📊🧪
Research Focus
Prof. Qinyu Ge’s research focuses on molecular biology, genomics, and bioinformatics 🧬🧪. His work explores transcriptomic analysis, environmental DNA (eDNA) applications, and non-invasive biomarkers for medical diagnostics 🧫🔬. He contributes to single-cell data analysis, DNA data storage, and the use of deep learning in predicting transcription factor binding sites 🤖📊. His studies cover areas like embryo selection, prostate cell typing, and neuroscience, including links to Parkinson’s disease 🧠🧍. By integrating advanced sequencing techniques with AI-based models, Prof. Ge enhances our understanding of gene expression, disease mechanisms, and biological data analysis. 🌍📈
Publication Top Notes
Acquisition and transcriptomic analysis of tissue micro-regions using a capillary-based method
Environmental DNA integrity index is sensitive for species biomass estimation in freshwater
The biological characteristics of long cell-free DNA in spent embryos culture medium as noninvasive biomarker in in-vitro embryo selection
Performance analysis of markers for prostate cell typing in single-cell data
Advances and Challenges in Random Access Techniques for In Vitro DNA Data Storage
Spatial transcriptomic profiling of isolated microregions in tissue sections utilizing laser-induced forward transfer
Transcriptome Study of rd1Mouse Brain and Association with Parkinson’s Disease
Effect of Different Staining Methods on Brain Cryosections
Prediction of Transcription Factor Binding Sites on Cell-Free DNA Based on Deep Learning
Deep-Cloud: A Deep Neural Network-Based Approach for Analyzing Differentially Expressed Genes of RNA-seq Data