UNLABELLED The recent explosion of comparative genomics data presents an unprecedented opportunity to construct gene networks via the evolutionary rate covariation (ERC) signature. ERC is used to identify genes that experienced similar evolutionary histories, and thereby draws functional associations between them. The ERC Analysis website allows researchers to exploit genome-wide datasets to in...

Gene regulatory networks (GRNs) represent dependencies between genes and their products during protein synthesis at the molecular level. At the present there exist many inference methods that infer GRNs form observed data. However, gene expression data sets have in general considerable noise that make understanding and learning even simple regulatory patterns difficult. Also, there is no well-k...

In synthetic biology, we need not only to design the basic functional modules, but also to understand the parameters of the designed modules. In this area, the existing theoretical result about periodic oscillation is difficult to achieve. We study the Piecewise Linear three-gene regulatory network with negative feedback loop to show how to control the periodic oscillation.

A key objective of gene network modeling is to develop intervention strategies to alter regulatory dynamics in such a way as to reduce the likelihood of undesirable phenotypes. Optimal stationary intervention policies have been developed for gene regulation in the framework of probabilistic Boolean networks in a number of settings. To mitigate the possibility of detrimental side effects, for in...

Gene Regulatory Networks (GRNs) consisting of combinations of transcription factors (TFs) and their cis promoters are assumed to be sufficient to direct the development of organisms. Mutations in GRNs are assumed to be the primary drivers for the evolution of multicellular life. Here it is proven that neither of these assumptions is correct. They are inconsistent with fundamental principles of ...

Gene regulatory networks (GRNs), when solved, provide immediate and predictive access to the specific functional termini at which genomic sequence determines the logic of the organismal regulatory system. GRN topology explains the fundamental processes of development (1), including dynamics (2), major evolutionary transitions (3), many aspects of physiological function, and normal and diseased ...

Evolvability is the capacity of a genotype to rapidly adjust to certain types of environmental challenges or opportunities. This capacity, documented in nature, reflects foresight enabled by the capacity of evolution to capture and represent regularities not only in extant environments, but in the ways in which the environments tend to change. Here we posit that evolvability substantially benef...

tification of gene regulatory networks by strategic gene disruptions and gene overexpressions. A system for identifying genetic networks from gene expression patterns produced by gene disruptions and overexpressions. approach to reconstructing genetic regulatory networks with hidden factors. [9] Allister Bernard and Alexander J Hartemink. Informative structure priors: joint learning of dynamic ...