I am currently an assistant research fellow at the Institute of Statistical Science of Academia Sinica. My research interests focus on three topics in computational biology: 1) Understanding the cross-talks of major signaling and regulatory pathways in cancer, 2) Studying the coupled evolution between components in biomolecular systems, 3) Integrating multiple sources of information to reconstruct the networks of gene regulation and their coupling with other systems, and suggesting new experiments to validate or disambiguate inferred models. Specifically, by examining the data of somatic mutations in cancer, we found that the same set of signaling pathways exhibit qualitatively different couplings in different tumor tissues (FASEB J. 2008). We built a computational model that identifies coevolving nucleic or amino acids from aligned sequences of multiple species. This model can capture different types of interactions (RNA-RNA, amino acid-amino acid, etc.), incorporates phylogenetic information, and requires very few extra free parameters. Using this model, we successfully detected RNA secondary and tertiary interactions (Mol. Biol. Evol. 2007) and established a compendium of coevolving positions among all the known protein domains (PLoS Comp. Biol. 2007). We developed a modeling framework to integrate the data of protein-protein, protein-DNA interactions and knock-out gene expression to identify the “active pathways” that may propagate the knock-out effects to downstream genes (JCB 2004), and validated the pathway models by new knock-out experiments suggested by an information theoretic criterion (Genome Biol. 2005). We further extended this modeling framework to capture the combinatorial regulation of multiple transcription factors (JCB 2006) and the coupling between gene regulation and metabolic reactions (BMC Bioinformatics 2006).