College of Medicine
Xie Lab
Led by Mingyi Xie · Biochemistry and Molecular Biology
What we study
The Xie Lab studies microRNAs and RNA modifications to understand their role in cancer and neurodegenerative diseases. They investigate mechanisms like microRNA degradation and RNA methylation in diseases like colorectal cancer and lung cancer.
What working here is like
- Wet lab
- Computational
- Cells in a dish
- Coding required
- Projects
- 7
- Papers
- 5
Current projects
Decipher microRNA mis-regulation in Colorectal Cancer via Semantic Embedded Graph Neural Networks
Using graph neural networks to study microRNA mis-regulation in colorectal cancer.
The molecular basis of 7SK RNA methylation in non-small cell lung cancer
Examining RNA methylation in lung cancer and its therapeutic potential.
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Molecular mechanisms for regulating microRNA levels in metazoans
Studies how cells keep microRNA levels in balance, including how these small regulatory RNAs are degraded, because their misregulation is linked to cancer and brain disease.
Exploring microRNA degradation in T-cell acute lymphoblastic leukemia
Studying microRNA degradation in T-cell acute lymphoblastic leukemia.
MicroRNA turnover induced by target RNAs in Colorectal Cancer
Investigating how target RNAs degrade microRNAs in colorectal cancer.
Unraveling circRNA and miRNA Expression in Alzheimer’s Disease Using Induced Pluripotent Stem Cells
The lab uses stem cells from Alzheimer’s patients and healthy people to compare levels of circular RNAs and microRNAs. They treat RNA to keep only circular forms, sequence them, and found at least ten circular RNAs that differ between disease and control. They will also measure microRNA levels later.
From the Spring 2025 UF Undergraduate Research Symposium · abstract book, p. 449
Mapping and Profiling N6-Methyladenosine Sites in 7SK Small Nuclear RNA
The lab maps where the chemical modification m6A occurs on the 7SK snRNA in lung cancer cells. Students will use SELECT‑qPCR and GLORI to identify modified sites and study their effect on RNA structure.
From the Spring 2025 UF Undergraduate Research Symposium · abstract book, p. 362
Summaries are written by AI in plain language from public symposium abstracts and may be imperfect.
Recent papers, explained
- scDeepAPA: a deep learning framework for single-cell alternative polyadenylation identification
2026 · Briefings in Bioinformatics
Makes a tool to find and study different RNA endings in single cells.
- GIN-CRC-Pareto: A graph-based pareto-optimized multi-task learning framework to identify miRNA-target interactions in colorectal cancer
2026 · Journal of Biomedical Informatics
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- CLASHub is an integrated database and analytical platform for microRNA-target interactions
2026 · Nature Communications
Creates a tool to study how tiny RNA molecules control gene activity.
- VIRSE: a variational Bayesian framework for RNA structural ensemble inference
2026 · Briefings in Bioinformatics
Develops a method to predict RNA shapes using new technology.
- A Myocyte‐Enriched Long Non‐Coding RNA NRMLncR Enhances Myogenesis in Mouse
2026 · The FASEB Journal
Finds a muscle-related RNA that helps muscle cells grow in mice.
Plain-language summaries are AI-written and reviewed by us; check the paper for details.
How to reach out
Mingyi Xie hasn't set up this page yet. Their UF Scholars profile lists their publications.