The well-known regulative properties of the sea urchin embryo, coupled with the recent elucidation of gene regulatory networks (GRNs) that underlie cell specification, make this a valuable experimental model for analyzing developmental plasticity. In the sea urchin, the primary mesenchyme cell (PMC) GRN controls the development of the embryonic skeleton. Remarkably, experimental manipulations r...

The efficacy of a newly created software package for predictive modeling of developmental gene regulatory networks (GRNs) has recently been demonstrated (Peter et al., 2012 ). The program GeNeTool computes spatial gene expression patterns based on GRN interactions and thereby allows the direct comparison of predicted and observed spatial expression patterns. GeNeTool also permits in silico expl...

The co-regulation of transcription factors (TFs) has been widely observed in various species. Why is such a co-regulation mechanism needed for transcriptional regulation? To answer this question, the following experiments and analyses were performed. First, examination of the human gene regulatory network (GRN) indicated that co-regulation was significantly enriched in the human GRN. Second, ma...

3 We propose a method to build gene regulatory networks (GRN) capable of 4 representing time-delayed regulations. The gene expression data is repre5 sented in a linear model using a dynamic Bayesian network (DBN) and a 6 skip-chain model using a hidden Markov model. The method therefore finds 7 both shortand long-term regulatory interactions. The algorithm was tested 8 on time-series data of th...

The neural crest, a multipotent embryonic cell type, originates at the border between neural and nonneural ectoderm. After neural tube closure, these cells undergo an epithelial-mesenchymal transition, migrate to precise, often distant locations, and differentiate into diverse derivatives. Analyses of expression and function of signaling and transcription factors in higher vertebrates has led t...

The interaction mechanisms at the molecular level that govern essential processes inside the cell are conventionally modeled by nonlinear dynamic systems of coupled differential equations. Our implementation adopts an S-system to capture the dynamics of the gene regulatory network (GRN) of interest. To identify a solution to inverse problem of GRN parameter identification the gravitational sear...

Gene regulatory networks (GRNs) are critical for dynamic transcriptional responses to environmental stress. However, the mechanisms by which GRN regulation adjusts physiology to enable stress survival remain unclear. Here we investigate the functions of transcription factors (TFs) within the global GRN of the stress-tolerant archaeal microorganism Halobacterium salinarum. We measured growth phe...

The sea urchin oral ectoderm gene regulatory network (GRN) model has increased in complexity as additional genes are added to it, revealing its multiple spatial regulatory state domains. The formation of the oral ectoderm begins with an oral-aboral redox gradient, which is interpreted by the cis-regulatory system of the nodal gene to cause its expression on the oral side of the embryo. Nodal si...

In Systems Biology, the complex relationships between different entities in cells are modeled and analyzed using networks. Towards this aim, a rich variety of gene regulatory network (GRN) inference algorithms has been developed recent years. However, most rely solely on expression data to reconstruct network. Due possible profile similarity, predictions can contain connections biologically unr...

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 ...