Computational & Systems Biology

Systems biology is the study of dynamic operations of biological networks ranging from protein-protein interaction networks to transcriptional regulatory, signaling, metabolic, and epigenetic regulatory networks. Systems biology and medicine approaches involve the following three cardinal features: 1) Production of comprehensive global data using genomic and proteomic technologies, including DNA sequences (SNP, CGH, somatic mutations), mRNA, protein (abundances, and PTMs- phosphorylation and acetylation, etc.), and metabolite data; 2) Reconstruction of network models representing key pathways underlying cellular processes of interest by integrating an array of global data; and 3) Generation of network-driven hypotheses for mechanisms for cellular processes of interest by analyzing the network models and then experimentally testing the network-driven hypotheses. Thus, the future of systems biology lies not only in improved technologies and methods for generation and integrated analysis of multiple types of global data, but also in the development of entirely new approaches to network modeling and experimental validation.

Computational

Daehee Hwang
Hong Gil Nam
June M. Kwak
Hye Ryun Woo