Gen düzenleme ağlarında uyumlu örgütlenme

With mounting information on details of biological networks, the interplay between structure and function has become a fertile field of research. For example, a power-law distribution of neighbor counts (or scale-freeness, an all-pervasive feature across biological and artificial networks) has been shown to promote robustness against internal or external influences, the abundance of certain substructures in intracellular networks can be linked with special tasks, the number of dynamical attractors (in correspondence with the number of cell types) can be predicted from the number of nodes and edges, etc. In this thesis, we introduce a novel measure of coherence for dynamic networks which encompass both activatory and repressory interactions. We investigate the degree of coherence, i.e., the unity of purpose between the simultaneously active regulatory agents with a common target, in gene regulatory networks responsible for cell cycle and cell differentiation in several organisms. Upon comparison with carefully chosen null-model ensembles, we demonstrate that these biological networks are, in fact, biased towards high coherence. We argue that this skewness is selected for by evolutionary pressures (akin to Hebbian selection in neuronal connections), under a demand for economical consumption of materials and energy available to the cell. The dependence of coherence on various structural parameters, such as the mean number of inputs per node and the activatory/repressory interaction ratio, as well as on dynamically determined quantities, such as the basin size and the number of expressed genes, is also investigated.