Research Interests

Complex human diseases, especially cancer, severely threaten human health and life worldwide. The underlying mechanisms of these diseases and drug resistance are still poorly understood. With the blooming of high-throughput techniques, the "big data" provide an unprecedented opportunity for the diagnosis, prognosis, and treatment of these diseases. Our research focus on developing computational approaches and tools to identify the biomarkers for human diseases, predict the novel drug targets and drug repositioning.

1. Non-coding RNAs:  Non-coding RNAs (ncRNAs) comprise multiple classes of RNA transcripts, such as microRNA (miRNA) and long non-coding RNA (lncRNA), that are not transcribed into proteins but have been shown to regulate the transcription, stability or translation of protein-coding genes. Current interests of our group are identification of miRNA and lncRNA biomarkers for cancer diagnosis, prognosis, and drug resistance, prediction of drug targeted miRNAs, and investigation of the role of lncRNA as competing endogenous RNA (ceRNA) in human cancers.

2. Computational pharmacogenomics: Drug discovery is time-consuming and tremendously expensive. In addition, chemoresistance is also a major obstacle in cancer treatment. How to select the most effective chemotherapy agents for individual patients is still a huge challenge. Drug repositioning, which can renew a failed drug or expand new indications for an existing drug, has attracted more attentions in drug development. Our group is currently focused on the identification of novel drug targets (drug targeted miRNAs) and novel drug candidates, and investigation of the mechanisms of drug side effects. We are also interested in predicting new drug combinations for treatment of chemoresistant patients and new therapeutics to target and destroy cancer stem cells.

3. Cancer Systems Biology: The dynamic process in the onset and progression of cancer is more complicated than we thought. Many factors, such as genetic, epigenetic or environmental changes, and their interactions contribute to the tumorigenesis and metastasis. The holistic view is essential in the study of human cancers. Our group is devoted to identify the biomarkers for diagnosis and prognosis of cancer, explore how perturbations of cellular networks lead to cancer, and investigate the pathogenesis of cancer from inflammation and development viewpoints. To achieve this, we propose systems biology approaches to integrate multi-level information, such as gene, miRNA, lncRNA, mutation, and methylation, into the protein-protein interaction network (PPIN) and transcriptional and post-transcriptional regulatory network.

4. Bioinformatics tools:  The "big data" analysis needs substantial knowledge of mathematics, computer science and statistics. In order to facilitate the biologists and clinicians analyze, interpret, and visualize the complex multi-omics data, we try our best to develop the bioinformatics tools and resources with user-friendly interface that can be used independently by biologists and clinical researchers.