Sandra Porter is having fun collecting all the new-fangled biological subdisciplines that end with “-omics”. The final product of each such project also has a name, ending with “-ome”.
You have all heard of the Genome (complete sequence of all the DNA of an organism) and the Genomics (the effort to obtain such a sequence), but there are many more, just look at this exhaustive list! In my written prelims back in 1999, I suggested that sooner or later there will be an organismome…until someone whispers that the term “physiology” already exists.
There are a couple of things that strike me when looking at such a long list of omes and omics’.
First, the fact it does not end with “-ology” suggests that the endeavor is not a study in order to understand, but an endeavor to complete a collection and tabulate all the items. I am not saying this is not science – not everything in science is “hypothesis testing” as your Intro textbooks erroneously tell you. It is just a different kind of scientific method. The idea is that collecting and tabulating all the elements in the system will allow for hypothesis-testing later in the future. It is providing important tools for future understanding. In other words, a system needs to be described before one can start trying to explain it.
Second, with a couple of exceptions, all the omes are collections of molecules, be it DNA, RNA, proteins, or the particular configurations of those molecules, or patterns of gene expression, etc. Behaviorome is one of such exceptions. Biome is another, though its inclusion on the list is probably incidental – its “ome” ending, when it was initially introduced back in 1916, had a different philosophical connotation in the spirit of the science of the times. Economics is on the list only because the person compiling the list had a sense of humor, of course (or is it?!).
In any case, each -ome is a collection of something physical. Perhaps a ‘skeletome’ could be the name for the collection of all the bones in a body…oh, wait! It is also a collection of parts that make up the system. This last sentence leads to the question posed by RPM: is a person doing some kind of “-omics” inevitably a reductionist?
Well, what is a reductionist? Many have written about this problem and giving it different names, usually not in a binary form but a triad, e.g., philosophical (or “vulgar”) reductionism, methodological reductionism and holism. Of all the treatments of scientific methodologies, I most like Robert Brandon’s analysis, in the last chapter of his 1995 book Concepts and Methods in Evolutionary Biology. It is not available online, but here is an article (PDF) that discusses it pretty fairly. I have also written about this issue before. Briefly:
– a holist refuses to “dissect” the system, choosing to study it as a whole only, arguing that breaking it apart is misleading and does not explain how the whole works.
– a philosophical reductionist supposes that phenomena observed at one hierarchical level can be explained by the identification of parts at the next lower level (you can see how easily this can slide into genetic determinism, as it denies or ignores emergent properties of the system).
– a methodological reductionist understands that “upward causation” is erroneous and pays more attention to the “downward causation”. A complex problem (not neccessarily a complex system) is broken down into manageable sub-problems (not neccessarily parts) that can be studied easily and can provide clear-cut data. Emphasis is more on the nature of interactions between elements of the system than the identity of the elements. However, knowing the identity of the elements allows one to recognize, tag and follow the elements as they interact with each other, thus revealing the rules of such interactions. Thus, having a Genome handy is a great tool for the study of interactions between molecules inside the cells, but the Genome in itself is un-informative.
So, two genomics researchers working side by side may differ – one being a philosophical, the other a methodological reductionist – depending on the understanding of the work they are doing: is sequencing a genome an end in itself, supposed to miraculously reveal the Mysteries Of Life (The Holy Grail, the Blueprint of Life), or is it building a tool for some exciting research to be done in the future.
Third thought that struck me as I glanced over the long list of omes and omics is that each ome, i.e., each collection of the parts, can be obtained by killing or freezing an organism (or organ, or cell, or ecosystem) and using various techniques to count and identify chemicals (or other parts) found in it. Even embryogenomics is concerned with gene expression at a particular time in development, primarily in order to “catch” the elusive genes – those that are not expressed in the adult.
The only ‘ome’ that cannot be studied this way but HAS to be studied in a living, breathing organism over time is Chronome:
Chronome n. The full complex of rhythms and temporal trends in an organism. The chronome consists of a multi-frequency spectrum of rhythms, trends, and residual structures, including intermodulations within and among physiological variables as well as changes with maturation and aging. // adj. = chronomic.
You can do a Google or Google Scholar search to see how much it is actually used in the (human/medical) chronobiological literature and in what context. I was surprised myself!
chronome = about 380 July 11, 2002, about 920 Aug. 10, 2005, about 18,400 Oct. 25, 2006
chronomics = about 42 July 11, 2002, about 423 Aug. 10, 2005, about 737 Oct. 25, 2006
Here is a bit longer description:
chronome: Derived from chronos (time), nomos (rule, law) and in the case of biological chronomes, chromosome, describes features in time, just as cells characterize the spatial organization of life. The chronome complements the genome (derived from gene and chromosome). The chronome consists of 1) a partly genetic, partly developmental, partly environmentally influenced or synchronized spectrum of rhythms; 2) stochastic or deterministic chaos; 3) trends with growth, development, maturation and aging in health and/ or trends with an elevation of disease risk, illness and treatment in disease; and 4) unresolved variability. The chronome is genetically coded: it is environmentally synchronized by cycles of the socio- ecologic habitat niche and it is influenced by the dynamics of the interplanetary magnetic field. The chronome constituents, the chrones, algorithmically formulated endpoints, are inferentially statistically validated and resolved by the computer. Chronomes and their chrones 1) quantify normalcy, allowing an individualized positive health quantification; 2) assess, by their alterations, the earliest abnormality, including the quantification of an elevated risk of developing one (or several) disease(s), chronorisk, by the alteration of one or several chrones; and 3) provide, by the study of underlying mechanisms, a rational basis in the search for measures aimed at the prevention of any deterioration in properly timed, mutually beneficial environmental- organismic interactions. [Franz Halberg et. al “The Story Behind: Chronome/ chrone” Neuroendocrinology Letters 20: 101 1999] http://www.nel.edu/20_12/nel20_12%20Chronome%20Chrone.htm
Gubin D, Halberg F. et. al, “The human blood pressure chronome: a biological gauge of aging” In Vivo 11 (6): 485- 494, Nov- Dec. 1997
Google = about 494 May 8 2003; about 16,800 Nov 10, 2006
chronomics: Technology allows the monitoring of ever denser and longer serial biological and physical environmental data. This in turn allows the recognition of time structures, chronomes, including, with an ever broader spectrum of rhythms, also deterministic and other chaos and trends. Chronomics thus resolves the otherwise impenetrable “normal range” of physiological variation and leads to new, dynamic maps of normalcy and health in all fields of human endeavor, including, with health care, physics, chemistry, biology, and even sociology and economics. [F. Halberg et. al. “Essays on chronomics spawned by transdisciplinary chronobiology. Witness in time: Earl Elmer Bakken” Neuroendocrinology Letters 22 (5): 359- 384 Oct. 2001]
Google = about 184 May 8, 2003, about 412 Aug. 17, 2005; about 768 Nov 10, 2006
Narrower terms: bacterial chronomics, cardio-chronomics
The term ‘chronome’ was coined by Franz Halberg, the same guy who coined the word “circadian”. This paper is freely available so you can see what it is all about. Frankly, the idea of collecting all temporal/rhythmic phenomena in the human body in health and disease sounds like a good idea for medical purposes. On the other hand, making such collections for other organisms does not make too much sense – we want to know the hows and whys of biological timing and using a couple of well-defined rhythms as markers is sufficient for such an endeavor as well as much more economical. Also, if you pore over that paper, you will see that Halberg is, in some places, pushing too hard and too far. To be perfectly honest, I do not believe all of the data presented in that paper and do not see the utility of much of his philosophizing either.
For an evolutionary/ecological/comparative chronobiologist, chronomics has little or no utility. On the other hand, I’d love to have a genome, transcriptome and proteome available for the critters I study – those would be super-useful tools.
Nice breakdown! And you found validation in the Googleome no less!
Googleome! Oh, no, my headdome is exploding!
Provided one can pick a useful cost metric, economics can be used to develop models that answer questions about resource competition, decision making, and many other useful things. I get the impression (I’m not an economist or a scientist) picking an appropriate cost metric is hard, assigning representative costs is harder, and that it’s all too easy to fall into the trap of thinking one’s economic model includes all the relevant properties of the system being modeled, but it’s still a useful field.
Those of us outside the field often forget that our negative opinions of it are strongly influenced by the most vocal and popular economists, all too many of whom are either kooks (Lott, Simon), or well-funded frauds.
(When I look at economics, I often feel as if I can find only the Pat Michaels and Fred Singers of the field, and not the Jim Hansens or Lonnie Thompsons.)
Is economics science? Jury is still out on this question (and it gets re-hashed regularly in blogs). While Nobel Prize-winning stuff may be, teh stuff taught in ECON101 is almost certainly not, and it is most certainly just plain wrong, leading so many people to have a basic misunderstanding of economics for the rest of their lives (unless they major in economics).
But, more to my point, economics is not an endeavor trying to collect and tabulate any elements. Thus, it is an odd one out on this list even if it is a science.
I appreciate all these data collections because at best they offer some interesting data. Howeve, I have some concerns about -omics:
On the one hand the tools to analyse or even just to extract data aren’t developing as fast as the amount of data increases.
Another thing I that puzzles me more is if -omics are real science. In the momment they tend to be just data collections that are piled up. This approach lacks one hallmark of science: They are not hypothesis driven. Thus, there is a danger of -omics to just end in themselves. To defend this approach -omics proponents in our institute allways claim that -omics will generate hypotheses (sic! the method will do this not the researcher). I wouldn’t care too much about that as such. However, -omic approaches are very expensive and they compete with smaller hypothesis driven research proposals. Unfortunately, funding agencies seem to have a tendency to misunderstand expensive research with “Big Science”. Thus many good “convetional” proposals remain unsurpoted.
Another issue that worries me is the position of the single scientist or PhD student in such projects. Due to the deficit in hypotheses it is hardly possible for students to learn the scientific method in such projects. In addition it may be difficult for scientists to develop their own scientific profile when they participate in such huge projects.
I see it as something more like mathematics – a tool for developing models used in science, but, not, in and of itself, science. But that’s just my own ignorance speaking.
Agreed. I think I got carried away and pounded out some reflexive response, rather than really thinking about your point, sorry.
Pingback: Observations: Circadian clock without DNA–History and the power of metaphor | StephenKMackSD's Blog