I Reverse engineering of gene networks. 1 Introduction. 2 Methods. 2.1 Artificial datasets. 2.2 Collected data. 2.3 Similarity measures. 2.4 Criteria for algorithm comparison. 3 Results. 3.1 Comparison on scale-free and random artificial networks. 3.2 Discerning static and causal interactions. 4 Conclusion. II The role of mRNA stability in the coordination of the YMC. 5 Introduction. 6 Methods. 6.1 Data sources. 6.2 Time series analysis. 6.3 Least squares regressions. 6.4 Clusterization. 6.5 A minimal dynamical model. 7 Results. 7.1 HL and the short-period YMC. 7.2 A detailed functional analysis. 7.3 Regulation via TFs versus RBPs. 7.4 Double peak and anticorrelated isoenzymes. 7.5 A minimal input-output dynamical model for the unfolding cycle. 7.6 A common dynamical gene expression program. 8 Conclusion. III Chemical reaction network theory and its applications. 9 Introduction. 10 Background material. 10.1 Multigraphs. 10.2 Cycle spaces. 10.3 Injectivity. 10.4 Stability of dynamical systems. 10.5 Chemical reaction networks. 11 ERNEST Toolbox. 12 Fundamental cycles and monotonicity. 13 Conclusion. Bibliography.