Comparative analyses for plant virus-based cancer immunotherapy drug development
Omole, A. O., Newton, H. S., Cedrone, E., Nematpour, K., Xie, S., et al. (2025). Cell Biomaterials, 1(6), 100095.
CV
Education
- Ph.D., College of Biology, China Agricultural University, 2014
- B.S., Huazhong Agricultural University, 2009
Professional experience
- Bioinformatics Analyst IV, Frederick National Laboratory for Cancer Research
- Develops reproducible analysis systems for high-throughput sequencing, single-cell and multimodal assays, and research-core operations.
- Builds scientific software, production workflows, automated quality control, and documentation for researchers and analysts.
Teaching
- Analysis of Gene Expression Data (BIOI611), University of Maryland, Fall 2025
- Graduate instruction in short- and long-read transcriptomics, experimental design, differential expression, transcript discovery, and single-cell analysis.
Research and engineering interests
- Single-cell, multimodal, protein proximity, and spatial analysis
- DNA methylation, epigenomics, and direct-RNA modification analysis
- Scientific software, interactive visualization, and reproducible workflows
- Scalable computing, HPC, containers, testing, and documentation
Selected technologies
- Python, R, Python Shiny, Seurat, AnnData/H5AD, and Pixelator
- DuckDB, Parquet, Snakemake, Slurm, Docker, and Singularity/Apptainer
- Cell Ranger, Oxford Nanopore Dorado, Modkit, and sequencing quality-control tools
- Git, GitHub, automated testing, and documentation systems
Publications
Nanoparticles may influence mast cells gene expression profiles without affecting their degranulation function
Newton, H. S., Cedrone, E., Grunberger, J., Xie, S., et al. (2025). Nanomedicine, 66, 102818.
Diversity and selection analyses identify transmission-blocking antigens as the optimal vaccine candidates in Plasmodium falciparum
Ciubotariu, I. I., Broyles, B. K., Xie, S., et al. (2024). eBioMedicine, 106, 105227.
Transgenerational increases in DNA methylation in Arabidopsis plants defective in active DNA demethylation
Tang, K., Zhu, X., Xie, S., Lang, Z., & Zhu, J.-K. (2024). PNAS, 121(22), e2320468121.
Aging and obesity prime the methylome and transcriptome of adipose stem cells for disease and dysfunction
Xie, S., Choudhari, S., Wu, C.-L., Abramson, K., Corcoran, D., Gregory, S. G., Thimmapuram, J., Guilak, F., & Little, D. (2023). The FASEB Journal, 37(3), e22785.
ViewBS: a powerful toolkit for visualization of high-throughput bisulfite sequencing data
Huang, X., Zhang, S., Li, K., Thimmapuram, J., & Xie, S. (2018). Bioinformatics, 34(4), 708–709.
Transcriptome-wide high-throughput deep m6A-seq reveals unique differential m6A methylation patterns between three organs in Arabidopsis thaliana
Wan, Y., Tang, K., Zhang, D., Xie, S., Zhu, X., Wang, Z., & Lang, Z. (2015). Genome Biology, 16, 272.
Genome-wide high resolution parental-specific DNA and histone methylation maps uncover patterns of imprinting regulation in maize
Zhang, M., Xie, S., Dong, X., et al. (2014). Genome Research, 24(1), 167–176.