The Study Of Two Problems In Systems Biology

Life Science and Science of Complexity are both the most important researchareas in the21st century. Systems biology is the intersection of these two areas. Gen-erally speaking, Systems Biology aims at understanding the function of biologicalobjects at systems level, which needs to synthesize different methods to fulfill the in-tegration of data from different sources and finally models emergency phenomenon inbiological system.In the thesis, we will study two problems. One is the biclustering algorithmfor time-series gene expression data, the other is the Darwinian modeling circadianrhythm of the mammalian SCN. We will study these two problems with different ap-proaches, aiming at showing our thinking on the study approaches to problems inSystems Biology.The research background of the first problem is gene regulatory network infer-ence. Biclustering algorithms of time-series gene expression data try to find out thosegene groups within each group the expression of the genes are correlated within a spe-cific time interval. Inspired by a biclustering algorithm based on suffix tree, we pro-pose a new one. The gene expression data are firstly represented as weighted strings,then transformed into general weighted suffix tree. We find out the inner nodes ofthe given general weighted suffix tree give the bicluster results. Both time complex-ity and space complexity are linear. Furthermore, the algorithm can be generalizedsmoothly to more complex application backgrounds, including mismatch, alignmentscore matrix, etc. The algorithm provides a good solution to the gene expression databiclustering problem and lays a sound foundation for further research.The research background of the second problem is the mechanism of functionof complex systems. We conjecture that the Darwinian mechanism and Darwinianprocess are common in complex systems. We take circadian rhythm of mammalian SCN as an example to illustrate how this mechanism and process could play the rolein SCN. Circadian rhythm is perhaps one of the most common biological phenomenonemerging on different biological levels, ranging from biomedical processes to cell,organism, individual, population and ecological system. We introduce the frameworkof mechanism design problem rooted in economics into our model, and demonstrateSCN cells can fulfill their time-telling function by adopting the Darwinian processwhich is similar to the process of Evolution by Natural Selection. In particular, wegive a brand-new explanation of the light-induced Phase Response Curve under thismodel.