Integrative Analysis of Multi-dimensional OMICs Data for Regulatory Network Inference

Abstract

The advent of OMICs technologies, such as microarray/RNA-seq, next generation sequencing (NGS) and proteomics, is revolutionizing the way we are doing biology. Biomedical research is transforming from a single candidate gene approach to systems biology. This transition is characterized by heavy use of genomics at DNA, RNA and protein levels, and by high demand of bioinformatics tools to process these data. I will introduce several bioinformatics tools developed in my lab for integrative analysis of genomic data, such as the web server ChIP-Array to infer gene regulatory networks from combined ChIP-seq and transcriptome data, and its application to collaborative research. I will also introduce our databases, GWASdb and GWAS3D that utilize data from ENCODE and 1000 genomes projects to annotate and prioritize genetic variants from NGS and GWAS studies. Finally, I will introduce our recent discovery on how GWAS can help in drug discovery, and computational methods to prioritize causal variants with regulatory roles. All the tools developed by the lab are freely available at http://jjwanglab.org/.