We are bioinformatics group at UNIST.

Our research interests are as follows:
(1) Identifying molecular markers and their functional networks that are associated with disease by analyzing transcriptomic and genomic data
(2) Developing computational models and algorithms that impact bio-medical research
(3) Classifying disease subtypes or cell types using gene expression big data (microarray, RNA-seq, single cell)

To this aim, we analyze microarrays, RNA-seq, GWAS, and single cell data in an integrative manner.
We also use and develop machine learning methods for data processing, clustering, dimension reduction, and classification.

Current Topics of Interest:
· Development of single-cell data processing, clustering, and classification methods
· Biclustering analysis of transcriptome big data
· Pathway and network analysis of gene expression and GWAS data
· Detection of rare drivers in cancer by integrating mutation and expression
· Read count modeling and simulation of RNA-seq and single cell data
· Improving miRNA target prediction