Editing Bioinformatics (section)

==Analysis of cellular organization==
Several approaches have been developed to analyze the location of organelles, genes, proteins, and other components within cells. A [[gene ontology]] category, ''cellular component'', has been devised to capture subcellular localization in many [[biological database]]s.

===Microscopy and image analysis===
Microscopic pictures allow for the location of [[organelle]]s as well as molecules, which may be the source of abnormalities in diseases.

===Protein localization===
Finding the location of proteins allows us to predict what they do. This is called [[protein function prediction]]. For instance, if a protein is found in the [[Cell nucleus|nucleus]] it may be involved in [[gene regulation]] or [[RNA splicing|splicing]]. By contrast, if a protein is found in [[mitochondria]], it may be involved in [[Cellular respiration|respiration]] or other [[Metabolism|metabolic processes]]. There are well developed [[protein subcellular localization prediction]] resources available, including protein subcellular location databases, and prediction tools.<ref>{{Cite web |url=https://www.proteinatlas.org/humancell |title=The human cell |website=www.proteinatlas.org |access-date=2017-10-02 |archive-date=2 October 2017 |archive-url=https://web.archive.org/web/20171002215345/https://www.proteinatlas.org/humancell |url-status=live }}</ref><ref>{{cite journal | vauthors = Thul PJ, Åkesson L, Wiking M, Mahdessian D, Geladaki A, Ait Blal H, Alm T, Asplund A, Björk L, Breckels LM, Bäckström A, Danielsson F, Fagerberg L, Fall J, Gatto L, Gnann C, Hober S, Hjelmare M, Johansson F, Lee S, Lindskog C, Mulder J, Mulvey CM, Nilsson P, Oksvold P, Rockberg J, Schutten R, Schwenk JM, Sivertsson Å, Sjöstedt E, Skogs M, Stadler C, Sullivan DP, Tegel H, Winsnes C, Zhang C, Zwahlen M, Mardinoglu A, Pontén F, von Feilitzen K, Lilley KS, Uhlén M, Lundberg E | title = A subcellular map of the human proteome | journal = Science | volume = 356 | issue = 6340 | pages = eaal3321 | date = May 2017 | pmid = 28495876 | doi = 10.1126/science.aal3321 | s2cid = 10744558 }}</ref>

===Nuclear organization of chromatin===
{{main|Nuclear organization}}
Data from high-throughput [[chromosome conformation capture]] experiments, such as [[Hi-C (experiment)]] and [[ChIA-PET]], can provide information on the three-dimensional structure and [[nuclear organization]] of [[chromatin]]. Bioinformatic challenges in this field include partitioning the genome into domains, such as [[Topologically Associating Domain]]s (TADs), that are organised together in three-dimensional space.<ref>{{cite journal | vauthors = Ay F, Noble WS | title = Analysis methods for studying the 3D architecture of the genome | journal = Genome Biology | volume = 16 | issue = 1 | pages = 183 | date = September 2015 | pmid = 26328929 | pmc = 4556012 | doi = 10.1186/s13059-015-0745-7 | doi-access = free }}</ref>