On the basic computational structure of gene regulatory networks

We investigate the dynamical properties of the transcriptional regulation of gene expression in the yeast Saccharomyces Cerevisiae within the framework of a synchronously and deterministically updated Boolean network model. By means of a dynamically determinant subnetwork, we explore the robustness of transcriptional regulation as a function of the type of Boolean functions used in the model that mimic the influence of regulating agents on the transcription level of a gene. W...

Biological networks have evolved to be highly functional within uncertain environments while remaining extremely adaptable. One of the main contributors to the robustness and evolvability of biological networks is believed to be their modularity of function, with modules defined as sets of genes that are strongly interconnected but whose function is separable from those of other modules. Here, we investigate the in silico evolution of modularity and robustness in complex arti...

Gene regulatory networks are powerful abstractions of biological systems. Since the advent of high-throughput measurement technologies in biology in the late 90s, reconstructing the structure of such networks has been a central computational problem in systems biology. While the problem is certainly not solved in its entirety, considerable progress has been made in the last two decades, with mature tools now available. This chapter aims to provide an introduction to the basic...

We investigate the cycles in the transcription network of S. cerevisiae. Unlike a similar network of E. coli, it contains many cycles. We characterize properties of these cycles and their place in the regulatory mechanism of the cell. Almost all cycles in the transcription network of S. cerevisiae are contained in a single strongly connected component, which we call LSCC (L for ``largest''), except for a single cycle of two transcription factors. Among different physiological...

Network analysis became a powerful tool in recent years. Heat shock is a well-characterized model of cellular dynamics. S. cerevisiae is an appropriate model organism, since both its protein-protein interaction network (interactome) and stress response at the gene expression level have been well characterized. However, the analysis of the reorganization of the yeast interactome during stress has not been investigated yet. We calculated the changes of the interaction-weights o...

Gene regulatory dynamics is governed by molecular processes and therefore exhibits an inherent stochasticity. However, for the survival of an organism it is a strict necessity that this intrinsic noise does not prevent robust functioning of the system. It is still an open question how dynamical stability is achieved in biological systems despite the omnipresent fluctuations. In this paper we investigate the cell-cycle of the budding yeast Saccharomyces cerevisiae as an exampl...

Evolving biomolecular networks have to combine the stability against perturbations with flexibility allowing their constituents to assume new roles in the cell. Gene duplication followed by functional divergence of associated proteins is a major force shaping molecular networks in living organisms. Recent availability of system-wide data for yeast S. Cerevisiae allow us to access the effects of gene duplication on robustness and plasticity of molecular networks. We demonstrat...

This paper addresses the decomposition of biochemical networks into functional modules that preserve their dynamic properties upon interconnection with other modules, which permits the inference of network behavior from the properties of its constituent modules. The modular decomposition method developed here also has the property that any changes in the parameters of a chemical reaction only affect the dynamics of a single module. To illustrate our results, we define and ana...

Background: Previous studies have used different methods in an effort to extract the modular organization of transcriptional regulatory networks (TRNs). However, these approaches are not natural, as they try to cluster highly connected genes into a module or locate known pleiotropic transcription factors in lower hierarchical layers. Here, we unravel the TRN of Escherichia coli by separating it into its key elements, thus revealing its natural organization. We also present a ...

Standard techniques for studying biological systems largely focus on their dynamical, or, more recently, their informational properties, usually taking either a reductionist or holistic perspective. Yet, studying only individual system elements or the dynamics of the system as a whole disregards the organisational structure of the system - whether there are subsets of elements with joint causes or effects, and whether the system is strongly integrated or composed of several l...