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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 ...
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 biological network is a method of representing systems as complex sets of binary interactions or relations between various biological entities. [1] In general, networks or graphs are used to capture relationships between entities or objects. [1]
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 ...
Wagner's gene network model is a computational model of artificial gene networks, which explicitly modeled the developmental and evolutionary process of genetic regulatory networks. A population with multiple organisms can be created and evolved from generation to generation.
The concept of gene co-expression networks was first introduced by Butte and Kohane in 1999 as relevance networks. [6] They gathered the measurement data of medical laboratory tests (e.g. hemoglobin level ) for a number of patients and they calculated the Pearson correlation between the results for each pair of tests and the pairs of tests which showed a correlation higher than a certain level ...