-omics

Template:Inappropriate tone Informally, the English-language neologism omics refers to a field of study in biology ending in the suffix -omics such as genomics or proteomics. The related neologism omes addresses the objects of study of such fields, such as the genome or proteome respectively. Users of the suffix “-om-” frequently take it as referring to totality of some sort.

## Contents

* 1 Origin
* 1.1 Omes and Omics people
* 2 Acceptance
* 3 Some of the new "omes"
* 4 Speculative "omics" and "omes"
* 5 Unrelated words in -omics
* 6 References
* 7 See also
* 8 External links

## Origin

[edit | edit source]

The suffix “-om-” originated as a back-formation from “genome”, a word formed in analogy with “chromosome”.[1] The word “chromosome” comes from the Greek stems “χρωμ(ατ)-” (colour) and “σωμ(ατ)-” (body).[1] (Thus, had this word been well-formed, it would instead be “chromatosome”.[2]) Because “genome” refers to the complete genetic makeup of an organism, some people have made the inference that there exists some root, *“-ome-”, of Greek origin referring to wholeness or to completion, but such root is unknown to most or all scholars.[3].

Because of the success of large-scale quantitative biology projects such as genome sequencing, the suffix "-om-" has migrated to a host of other contexts. Bioinformaticians and molecular biologists figured amongst the first scientists to start to apply the "-ome" suffix widely.[citation needed]

### Omes and Omics people

[edit | edit source]

Template:Unreferencedsection Bioinformatists and molecular biologists figured amongst the first scientists to start to apply the "-ome" suffix widely. Some early advocates were bioinformatists in Cambridge, UK where there have been many early bioinformatics and omics related labs such as MRC centre, Sanger centre, EBI(European Bioinformatics Institute), Cavendish lab, genetics, and biochemistry departments. For example, MRC centre is where the first genome and proteome projects were carried out. EBI members were some of the earliest bioinformatists. For example, Christos Ouzounis's lab used the term textome. In the USA, due to the expansion of the internet, there were perhaps the largest number of bioinformatics and biology researchers who coined and used various omics such as phenome, physiome, metabolome, and so on.

In the mid 1990s, many scientists were not serious about omes and omics trend and jokingly talked about or playfully coined new omes and omics'. While some younger researchers took the terms seriously enough to organize and produce conceptual omes and omics en masse. This trend coupled by the trend of attaching bio- prefix to various biological and programming terms such as Bioperl and Biojava. There were a group of locally and internationally networked researchers who were proposing open and free style sharing information and programs. Jong Bhak was one of the enthusiastic takers of bio-, omes, and omics trend in Cambridge. Steve Brenner, George Fuellen, Ewan Birney, Chris Dagdigian, and several others were the young students who took up such Bio- projects and produced internationally collaborative bio- projects that affected the omics growth. Dan Bolser has advocated the concept of omics in complex systems perspective through interaction network research. In USA, George Church lab in Harvard medical school was an early advocate of conceptualizing omes and omics as shown in their web pages. In Yale, Mark Gerstein (who received his Ph.D. in MRC centre in Cambridge UK) was active in that trend, too. The historical observation showed one trend.

As research scientists increasingly sought to integrate biology with information science, they took up the use of omics. For biologists -omics easily conveyed a key concept, the implications of a complex systems approach, an approach that is closely tied to study of networks, emergent properties and encapsulation concepts of theoretical computer science. Information savvy biologists took up the ideas of Stuart Alan Kauffman's work. In 1999 and early 2000s, physicists and computer scientists produced some debatable papers on scale-free network properties in biological systems. These also contributed significantly in the expansion of the use of omics as a way to describe heterogeneous networks of objects.

## Acceptance

[edit | edit source]

Some “-ome” are becoming useful, beyond the original “genome”. “Proteomics” has become well-established as a term for studying proteins. Researchers have proposed other “-omes” which are becoming accepted within biology field. Omes and omics concepts provide a distinct knowledge layer for biologists, especially when they become interested in high throughput experimental analyses. Modern biology is becoming an information science and such omes and omics classification can provide skeletons for various previously less well defined fields. For example, the term genetic study in the past could mean many different things for many different scientists while interactome study clearly sub divides a genetic study to the gene-gene, protein-protein, or protein-ligand interactions in terms of large scale information processing to find some networked functional information. Omes and omics is one of the most convenient and extensive reformations of biology since evolution and inheritance concepts were proposed in mid 1800s and molecular sequences and structures were deciphered in 1960s and 1970s. Researchers are taking up the omes and omics very rapidly as shown in the use of the terms in Pubmed in the last decade.

## Some of the new "omes"

[edit | edit source]

* The transcriptome, the mRNA complement of an entire organism, tissue type, or cell; with its associated field transcriptomics[1]
* The metabolome, the totality of metabolites in an organism; with its associated field metabolomics[2]
* The metallome, the totality of metal and metalloid species; with its associated field metallomics
* The lipidome, the totality of lipids; with its associated field Lipidomics [3]
* The glycome, the totality of glycans, carbohydrate structures of an organism, a cell or tissue type. Glycomics: The associated field of study. See http://www.functionalglycomics.org.
* The interactome, the totality of the molecular interactions in an organism[4]; a once proposed field of interactomics[5] has generally become known as systems biology
* The spliceome (see spliceosome), the totality of the alternative splicing protein isoforms;[6] with its associated field spliceomics.
* The ORFeome refers to the totality of DNA sequences that begin with the initiation codon ATG, end with a nonsense codon, and contain no stop codon. Such sequences may therefore encode part or all of a protein.[7][8]
* The speechome. (BBC article on the Speechome Project)
* The mechanome refers to the force and mechanical systems at work within an organism.
* The Phenome \- the organism itself. The Phenome is to the genome what the phenotype is to the genotype. Also, the complete list of phenotypic mutants available for a species.
* The Exposome \- the collection of an individual's environmental exposures.[4]

## Speculative "omics" and "omes"

[edit | edit source]

* Textome: The body of scientific literature which text mining can analyse. Textomics: The study of the textome.
* Kinome: The totality of protein kinases in a cell. Kinomics: The study of the kinome. Publications exist.
* Physiome: Related to physiology. Physiomics: The associated field of study.
* Neurome: The complete neural makeup of an organism. A word which a neurobiologist might utter in the future. Neuromics: The study of the neurome.
* Note: Neurome[9] and Neuromics[10] are now the names of Biotech companies. The term 'Neurome' has been used by NeuronBank.org[11], which is an attempt to develop an approach to catalog the Neurome.
* Cytome: The cellular composition of a tissue. This term is associated to cell sorting techniques.
* Predictome: A complete set of predictions.[12]
* Omeome: A complete set of "omes", Omeomics will be the cataloguing of all "omics"
* Reactome: A knowledge base of biological processes.[13]
* Connectome: The connections between neurons. A Technicolour Approach to the Connectome (Nature)

## Unrelated words in -omics

[edit | edit source]

Note that “comic” does not exemplify this suffix; it derives from Greek “κωμ(ο)-” (merriment) + “-ικ(ο)-” (an adjectival suffix), rather than presenting a truncation of “σωμ(ατ)-”.

Similarly, the word “economy” is assembled from Greek “οικ(ο)-” (household) + “νομ(ο)-” (law or custom), and “economic(s)” from “οικ(ο)-” + “νομ(ο)-” + “-ικ(ο)-”. The suffix -omics is sometimes used to create portmanteau words to refer to schools of economics such as Reaganomics.

## References

[edit | edit source]

1. ↑ 1.0 1.1 Coleridge, H.; et alii. The Oxford English Dictionary
2. ↑ Smyth, Herbert Weir. Greek Grammar, Part III: Formation of Words
3. ↑ Liddell,, H.G.; Scott, R.; et alii. A Greek-English Lexicon [1996]. (Search at Perseus Project.)
4. ↑ Wild CP (2005). "Complementing the genome with an "exposome": the outstanding challenge of environmental exposure measurement in molecular epidemiology". Cancer Epidemiol. Biomarkers Prev. 14 (8): 1847–50. doi:10.1158/1055-9965.EPI-05-0456. PMID 16103423.

## See also

[edit | edit source]

* -ome
* List of omics topics in biology

## External links

[edit | edit source]

* Omics.org — The omics wiki site. A comprehensive omics list on the internet.
* List of omics — Lists far more than this page, with references/origins. Maintained by the (CHI) Cambridge Health Institute. One of the earliest lists.
* Omics World — Resources and information for omics research
* Lederberg J, McCray A. 'Ome Sweet 'Omics — A Genealogical Treasury of Words PDF (2 pages). The Scientist 15[7]:8, Apr. 2, 2001. Commentary.

de:-omik ko:체학 it:-omics nl:-omics sv:-omik