My research is focused on developing bioinformatics algorithms especially through sequencing analysis and data integration, to understand better transcriptional and epigenetic regulation. Transcription factor often binds to DNA and interferes with transcription machinery to enhance or repress gene expression. Epigenetic features such as histone modification, chromatin remodeling factor binding, DNA methylation, and chromatin 3D organization add yet another layer of information, making it more complex to understand the regulation dynamics within the nucleus. With advancing sequencing technology, however, such information now can be measured and quantified in genome scale, though the growing number of big genomic datasets creates challenges as well as opportunities for bioinformatics methodologies. The focus of our lab is to build algorithms, analysis platforms and databases to integrate big datasets from the public domain into various biological questions and disease models. The MACS (Genome Biology 2008) algorithm, on which I worked to develop, is one of the most widely-used algorithms for predicting cis-regulatory elements from Chromatin Immunoprecipitation with high-throughput sequencing (ChIP-seq). The algorithm has been evolving over years to accommodate various factor types from punctuate transcription factor binding to long-range histone modifications. It has been used to process hundreds of publicly-available datasets in the mod/ENCODE project, and it continues as a focus of my lab. I also worked to build an integrative platform for ChIP analysis based on Galaxy framework, named Cistrome (Genome Biology 2011). This platform provides both a user-friendly interface and rich functionality for biologists to manage and process their high-throughput genomic data and to publish the results conveniently over the Internet. The Cistrome platform will continue as a collaborative project between my UB lab and research partners at Harvard University.