고려대학교

초록/요약

In post-genomic era, the interests of biological research focus on understanding the manner in which cells execute and control the enormous number of operations required for normal function and the ways in which cellular systems fail in disease. So, systemic or network perspectives are becoming important in biological research because biological systems functions in integrated network of many components and their interactions among biochemical, regulatory and signaling pathways. By analyzing the networks of cellular components, we may acquire new insight about the functions of cell or biological system. This systemic analysis of cellular network is possible due to development of new technology which is producing much biological experimental data like genome sequence, protein-protein interaction map, and whole genome expression profile. Among the technologies, one of the highest-throughput method available today is microarray technology using high-density arrays of DNA on glass to measure gene expression levels on a genome scale. In this paper, we proposed novel method inferring the genetic regulatory network from cDNA microarray data of S. cerevisiae. Two different type of microarray data was used: one is gene disruption type data, the other is time-series data. Topology of the network was constructed from the gene disruption data and direction between nodes was done from the time-course data. This network which provides conceptual regulatory inference relation between genes may be used to model biological system and cellular behavior.