OUR RESEARCH FOCUS
Modulatory Interactions
Defining functional RNA-RNA, RNA-protein, and RNA-chromatin interaction networks of lncRNAs to understand their molecular mechanisms.
Cell Fate Determination
Investigating the roles of lncRNAs in cell identity maintenance and cell fate transitions, related to cell identity, development, and disease.
Predictions & Validation
Using computational and experimental approaches to predict and validate lncRNA functions and regulatory roles, including epigenetic regulation and gene expression control.
RECENT WORKS
Lab Article
A recent article presents a deep learning method to predict how long noncoding RNAs (lncRNAs) interact with proteins using only RNA sequence data. This method works across species, even when the lncRNA sequences are very different, helping to identify important functional sites. It provides a new way to study and understand many lncRNAs that have not been well characterized before.
Collaboration
An exciting collaboration has led to EssSubgraph (lead PI: Tian Hong at UT Dallas), which is an efficient machine learning method that integrates biological network and omics data to predict essential genes in mammals, showing generalizability compared to existing approaches.
Invited Paper
In this article, we call out the need for improved approaches to facilitate interdisciplinary collaboration and propose a web-based platform that uses social media tools and smart algorithms to help researchers from different fields connect and collaborate, overcoming barriers like cultural differences and power dynamics to foster sustained, innovative interdisciplinary research.