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Structure of a gene regulatory network Control process of a gene regulatory network. A gene (or genetic) regulatory network (GRN) is a collection of molecular regulators that interact with each other and with other substances in the cell to govern the gene expression levels of mRNA and proteins which, in turn, determine the function of the cell.
A gene regulatory network [20] is a set of molecular regulators that interact with each other and with other substances in the cell. The regulator can be DNA, RNA, protein and complexes of these. Gene regulatory networks can be modeled in numerous ways including; Coupled ordinary differential equations, Boolean networks, Continuous networks ...
Procedures to identify association, communities, and centrality within nodes in a biological network can provide insight into the relationships of whatever the nodes represent whether they are genes, species, etc. Formulation of these methods transcends disciplines and relies heavily on graph theory, computer science, and bioinformatics.
Regulation of gene expression, or gene regulation, [1] includes a wide range of mechanisms that are used by cells to increase or decrease the production of specific gene products (protein or RNA). Sophisticated programs of gene expression are widely observed in biology, for example to trigger developmental pathways, respond to environmental ...
Gene regulatory pathway. In genetics, a regulator gene, regulator, or regulatory gene is a gene involved in controlling the expression of one or more other genes. Regulatory sequences, which encode regulatory genes, are often at the five prime end (5') to the start site of transcription of the gene they regulate. In addition, these sequences ...
Gene regulatory network inference is a technique that aims to construct a network, shown as a graph, in which the nodes represent the genes and edges indicate co-regulatory interactions. The method relies on the assumption that a strong statistical relationship between the expression of genes is an indication of a potential functional ...
Models of the kinetics of proteins and ion channels associated with neuron activity represent the lowest level of modeling in a computational neurogenetic model. The altered activity of proteins in some diseases, such as the amyloid beta protein in Alzheimer's disease, must be modeled at the molecular level to accurately predict the effect on cognition. [1]
This is the simplistic DNA → RNA → protein pathway published by James Watson in the first edition of The Molecular Biology of the Gene (1965). Watson's version differs from Crick's because Watson describes a two-step (DNA → RNA and RNA → protein) process as the central dogma. [ 7 ]