Editing Gene expression (section)

==Gene networks==
{{main|Gene regulatory network}}
Genes have sometimes been regarded as nodes in a network, with inputs being proteins such as [[transcription factor]]s, and outputs being the level of gene expression. The node itself performs a function, and the operation of these functions have been interpreted as performing a kind of information processing within cells and determines cellular behavior.

Gene networks can also be constructed without formulating an explicit causal model. This is often the case when assembling networks from large expression data sets.<ref>{{cite journal | vauthors = Banf M, Rhee SY | title = Computational inference of gene regulatory networks: Approaches, limitations and opportunities | journal =  Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms| volume = 1860 | issue = 1 | pages = 41–52 | date = January 2017 | pmid = 27641093 | doi = 10.1016/j.bbagrm.2016.09.003 | doi-access = free }}</ref> Covariation and correlation of expression is computed across a large sample of cases and measurements (often [[transcriptome]] or [[proteome]] data). The source of variation can be either experimental or natural (observational). There are several ways to construct gene expression networks, but one common approach is to compute a matrix of all pair-wise correlations of expression across conditions, time points, or individuals and convert the matrix (after thresholding at some cut-off value) into a graphical representation in which nodes represent genes, transcripts, or proteins and edges connecting these nodes represent the strength of association (see [http://www.genenetwork.org GeneNetwork GeneNetwork 2]).<ref name="pmid 15114364">{{cite journal | vauthors = Chesler EJ, Lu L, Wang J, Williams RW, Manly KF | title = WebQTL: rapid exploratory analysis of gene expression and genetic networks for brain and behavior | journal = Nature Neuroscience | volume = 7 | issue = 5 | pages = 485–486 | date = May 2004 | pmid = 15114364 | doi = 10.1038/nn0504-485 | s2cid = 20241963 }}</ref>