Much effect has been devoted over the past decade to inference of gene regulatory networks (GRNs). However, the previous methods infer GRNs containing large amount of false positive edges, which could result in awful influence on biological analysis. In this study, we present a novel hybrid framework to improve the accuracy of GRN inference. In our method, network topologies from linear and non...

The advent of high-throughput technology like microarrays has provided the platform for studying how different cellular components work together, thus created an enormous interest in mathematically modeling biological network, particularly gene regulatory network (GRN). Of particular interest is the modeling and inference on time-series data, which capture a more thorough picture of the system ...

i is the current concentration of the protein i and is a function that keeps of the sum of all protein concentrations equal to 1. and ⇥ are two constants that set up the speed of reaction of the regulatory network. The higher these values, the more sudden the transitions in the GRN. The lower they are, the smoother the transitions are. Whereas the input proteins of a GRN can be used to describe...

This paper explores the application of an artificial developmental system (ADS) to the field of evolutionary robotics by investigating the capability of a gene regulatory network (GRN) to specify a general purpose obstacle avoidance controller both in simulation and on a real robot. Experiments are carried out using the e-puck robot platform. It is further proposed to use cross-correlation betw...

Head blight caused by Fusarium graminearum threatens world-wide wheat production, resulting in both yield loss and mycotoxin contamination. We reconstructed the global F. graminearum gene regulatory network (GRN) from a large collection of transcriptomic data using Bayesian network inference, a machine-learning algorithm. This GRN reveals connectivity between key regulators and their target gen...

Much laboratory work has been carried out to determine the gene regulatory network (GRN) that results in plant cells becoming flowers instead of leaves. However, this also involves the spatial distribution of different cell types, and poses the question of whether alternative networks could produce the same set of observed results. This issue has been addressed here through a survey of the publ...

Understanding the control of gene expression remains one of the main challenges in the post-genomic era. Accordingly, a plethora of methods exists to identify variations in gene expression levels. These variations underlay almost all relevant biological phenomena, including disease and adaptation to environmental conditions. However, computational tools to identify how regulation changes are sc...

The axial bodyplan of Drosophila melanogaster is determined during a process called morphogenesis. Shortly after fertilization, maternal bicoid mRNA is translated into Bicoid (Bcd). This protein establishes a spatially graded morphogen distribution along the anterior-posterior (AP) axis of the embryo. Bcd initiates AP axis determination by triggering expression of gap genes that subsequently re...

Understanding the functional relationship between intracellular factors and extracellular signals is required for reconstructing gene regulatory networks (GRN) involved in complex biological processes. One of the best-studied bilaterian GRNs describes endomesoderm specification and predicts that both mesoderm and endoderm arose from a common GRN early in animal evolution. Compelling molecular, ...