1. Develop an integrated model that incorporates epigenetic and other functional data. We develop and improve an integrated model that combines data from various sources to analyze and understand condition-specific biological phenomena. The goal of this integrated model is to reveal condition specific transcriptional regulation by combining chromatin signatures as well as DNA sequences and evolutionary information (Figure 1).
    Figure 1. Gene annotation by ChromModule reveals cell type specific gene regulation.
  2. Uncover combinatorial regulation between TFs and infer the transcriptional network structure One of the major challenges in the post-genome era is to reconstruct transcriptional network in a condition specific manner. Combining various sources of data, the new integrated model mentioned above will be used to tackle this problem. By defining a node as a TF or a gene and an edge as a regulatory interaction, a graph can represent the transcriptional network in a cell. The regulatory interactions can be inferred by using the integrated model to predict which TFs bind to which genes at a specific condition.
    Figure 2. The transcription factor network in embryonic stem cells.