The availability of huge omics data from genome projects and high-throughput technology (e.g. microarray, deep sequencing, and GWAS etc.) has brought a great challenge to researchers to understand to the complexity of biological process and disease mechanism. It is a great opportunity to integrate those data and study them at systems level using bioinformatics and systems biology methods.
Many genes and pathways involve in complex diseases and many high-throughput experimental approaches were applied in complex diseases. These provide an opportunity for bioinformatics to study complex disease at systems level. Our research interest is in using bioinformatics approaches to explore the molecular mechanisms of complex diseases (cardiovascular diseases, cancers and leukemia). This includes multiple data source integration, database construction, candidate gene selection, network and pathway analysis in disease. We focus on integrating regulatory network, protein-protein interaction, and pathway information in complex diseases.
Transcription factors and microRNAs are essential and important regulators for gene expression, we especially interest in the co-regulation network of transcription factors and microRNAs in complex diseases.
Currently, a huge amount of large scale data and genome sequences are available. Analyzing and mining these data to obtain useful information for biomedical research is one of the tasks of bioinformatics. We also interest in large scale data analysis (e.g. high-throughput sequencing) as well as the gene feature analysis, evolution and comparative genomics analysis of specific gene and gene family.