Editing Bioinformatics (section)

===Analysis of regulation===
[[Gene regulation]] is a complex process where a signal, such as an extracellular signal such as a [[hormone]], eventually leads to an increase or decrease in the activity of one or more [[protein]]s. Bioinformatics techniques have been applied to explore various steps in this process.

For example, gene expression can be regulated by nearby elements in the genome. Promoter analysis involves the identification and study of [[sequence motif]]s in the DNA surrounding the protein-coding region of a gene. These motifs influence the extent to which that region is transcribed into mRNA. [[Enhancer (genetics)|Enhancer]] elements far away from the promoter can also regulate gene expression, through three-dimensional looping interactions. These interactions can be determined by bioinformatic analysis of [[chromosome conformation capture]] experiments.

Expression data can be used to infer gene regulation: one might compare [[microarray]] data from a wide variety of states of an organism to form hypotheses about the genes involved in each state. In a single-cell organism, one might compare stages of the [[cell cycle]], along with various stress conditions (heat shock, starvation, etc.). [[cluster analysis|Clustering algorithms]] can be then applied to expression data to determine which genes are co-expressed. For example, the upstream regions (promoters) of co-expressed genes can be searched for over-represented [[regulatory elements]]. Examples of clustering algorithms applied in gene clustering are [[k-means clustering]], [[self-organizing map]]s (SOMs), [[hierarchical clustering]], and [[consensus clustering]] methods.