Research

Recent development of high-throughput technologies generate and continue to generate an overwhelmingly large amount of data. It provides both opportunities and challenges for knowledge discovery from genomic data. Sequence-based computational methods, as excellent complements to experimental techniques, provide a fast, efficient and cost effective solution to modeling genomic data, and revealing the underlying biological mechanisms.

Our research is about developing computational tools that can process and analyze various kinds of complex in genomics and proteomics data.

Our interest falls into the broad category of Bioinformatics. Some current projects include:

• Prediction of DNA regulatory elements such as nucleosome, origin of replications, tanscription start sites, promoter.


• Aanlysis of regulatory elements using nucleotide physicochemical properties.


• Designing computational method to predict RNA modification sites, RNA subcellular localization and RNA splicing.


• Developing machine learning methods to identify protein function and type.