-omics

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Informally, the English-language neologism omics refers to a field of study in biology ending in the suffix -omics such as genomics, transcriptomics, proteomics, or interactomics. Also, as a systems biology point of view, omics refers to the whole set of -omics subfields to understand the life as a holistic and organic being.
The related neologism omes addresses the objects of study of such fields, such as the genome, transcriptome, proteome, or interactome respectively. Users of the suffix “-om-” frequently take it as referring to totality of some sort.

Contents

Origin

The suffix “-om-” originated as a back-formation from “genome”, a word formed in analogy with “chromosome”.[1] The word “chromosome” of course 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. 

Omes and Omics People
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 center, EBI, Cavendish lab, genetics department, and biochemistry department. For example, MRC centre is where the first genome and proteome projects were carried out. EBI members were  some of the very earliest bioinformatists. For example, Christos  Ouzounis's lab used the term textome. In the mid 1990s, many scientists were not serious about omes and omics trend and jokingly talked about or playfully coined new omes. While some younger researchers took the terms seriously enough to organize and produce conceptual omes and omics terms en masse. Jong Bhak was one of the serious early takers of omes and omics trend in Cambridge. In USA, Church lab in Harvard medical school was an advocate of conceptualizing omes and omics. In Yale, Mark Gerstein (who received his Ph.D. in MRC centre in Cambridge UK) was active in that  field. The historical observation shows one trend. When researchers were aware of the trend that biology was becoming an information sicence, they took up the omics trend easily. It was because the concept of ome implies  some complex systems approach in theoretical computer science where networks, emergent properties and encapsulation concepts are the key ideas understanding life. In that sense, in computer science, people have been already running ahead of biologists in theoretical terms. Information savvy biologists took up the ideas of Steward Kauffman's work. In 1999 and early 2000s, physicists and computer scientists produced some debatable papers on scale-free netowork properties in biological systems. These also contributed a lot in the expansion of omics as the best way to describe heterogeneous networks of objects was to use omes.

Pseudo-omics and Nonsensomics
Omics is a progressive  and useful concept in biology. It can revolutionize the way biology is done and how we see life in the future. However, omics fields itself is under evolution and natural selection. Some  omics do not have livable niche. For example, translationomics does not have any distincive value at the moment while it should correspond to transcriptomics. As time goes by, practically useful omics will survive and go into the mainstream biology while some others will die out until revived in an unexpected way. These unviable omics can be collectively called pseudoomics and nonsensomics.

The difference among Omics, Bioinformatics and Systems Biology

Systems biology is “biology” that focuses on complex systems in life. Omics focuses on large scale and holistic data/information to understand life in encapsulated omes (in many distinct biolayers). Bioinformatics is an information science that analyzes life processes using computational tools for solving biological problems and give direction/overview in biology. See the definition of bioinformatics in Bioinformatics.ws


References

  1. ^ a b 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.)

Acceptance

Some “-ome” other than “genome” are becoming useful. “Proteomics” has become well-established as a term for studying the proteome. Researchers have proposed other “-omes” which are becoming accepted within biology as a whole. Omems 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 sicence 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 function information. Omes and omics is one of  the most convenient and extensive reformation of biology since evolution and inheritance conceptt  were proposed and molecular sequences and structures were deciphered. Researchers are taking up the omes and omics very rapidly as shown in the use of the terms in pubmed in the last decade.

We predict that biology will be restructured in the future by omes and omics concepts due to high throughput experimental technology and information technology.

Some of the new "omes"

  • 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 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 ORFome: same as ORFeome.
  • 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.

New "omics" and "omes"

  • 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.
  • Glycome: Related to glycosylation. Glycomics: The associated field of study.
  • 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.

  • Predictome: A complete set of predictions.[12]
  • Reactome: A knowledge base of biological processes.[13]

Unrelated words in -omics

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)-”.

See also

External links

  • Omics.org - The omics wiki site. One of the earliest omics lists on the internet.
  • List of omics — Lists far more than this page, with references/origins. Maintained by the Cambridge Health Institute.
  • Omics World – Resources and information for omics research
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