This talk is an attempt to address the following: 1. What are genetic interactions and genetic networks? 2. Why inferring genetic network is one of the frontier areas in computational biology? 3. How statistical modeling and computational algorithms pave the way to infer complex molecular mechanism, e.g. biochecmical pathways central to diseases, from genomics data. In particular, how reducing ten-thousands of potential interactions to tens can be achieved. Some algorithms developed by my team will be briefly introduced (PARE Bioinformatics, 2008, WebPARE, Bioinformatics, 2010; AdaFuzzy, BMC Bioinformatics, 2009, GASA, BMC Systems Biol., 2010), as compared to some relevant well-known algorithms. Applications to infer transcriptional compensation interactions in yeast and transcriptional interactions involved in differentiation of pre-adipocytes (obesity) in human (a collaboration with INSERM, France) will be illustrated. Lab presentation Some projects from domestic and international collaborations will be presented, which include epigenetics in yeast, a large set of genetic interactions in yeast screened by SGA technology (Boone lab), transcriptional interactions involved in HBx induced liver cancer in mouse.