Are We Misinterpreting Plant Single-Cell Data? Rethinking Analysis Strategies for Non-Model Plant Species
Sponsor(s): Computational Biology and Bioinformatics (CBB), Biology, Biomedical Engineering (BME), Biostatistics and Bioinformatics, Center for Advanced Genomic Technologies, Duke Center for Genomic and Computational Biology (GCB), Molecular Genetics and Microbiology (MGM), Neurobiology, Program in Cell and Molecular Biology, School of Medicine (SOM), and University Program in Genetics & Genomics (UPGG)
The Li lab focuses on developing computational frameworks to overcome fundamental barriers in plant single-cell genomics, particularly for non-model organisms. By integrating enhanced genome annotations, rigorous benchmarking of analytical methods, and cross-species marker gene mapping, my work aims to improve the accuracy and scalability of single-cell data interpretation. These approaches ultimately seek to enable more reliable comparative analyses across diverse plant species, facilitating the transfer of biological insights from model systems to crops and other understudied species.
Type: MEDICINE, ENGINEERING, NATURAL SCIENCES, LECTURE/TALK, PANEL/SEMINAR/COLLOQUIUM, RESEARCH, and TECHNOLOGY
Contact: Monica Franklin





