I am getting annoyed at all those “-omes” and -“omics”!

I am very, very sorry, but I am sick of all those “-omes” and -“omics”…

I have said more than once that nature, especially the biology part, is majestic.  In all fairness, the “…especially the biology…” phrase illustrates my bias for the living world.  However, in reality, it is important to realize that the usual subdivisions in which we classify science are fundamentally artificial.  We simply cannot understand biology without understanding chemistry, for which we must understand physics, which in turn cannot make sense without using mathematics and finally, some argue that mathematicians only answer to God…

Science is going through a very weird phase in its development.  I am not the first one to say this, by the way.

Traditionally, science tends to be hypothesis-driven, usually sparked by a little bit of data, this is, an observation of some kind.  Isaac Asimov said something in the lines of “The most exciting phrase to hear in science, the one that heralds new discoveries, is not ‘Eureka!’ (I found it!) but ‘That’s funny …’

This means that a curious observation can make the proverbial wheels of a mind turn.  It can make yourself think “What if?”

The question What if? is the beginning of a hypothesis. Essentially, in science a hypothesis is an “educated guess” about how something works.  Usually we can articulate a hypothesis as something like “If I do X, then Y should happen“.  The beauty of this is that whether we are right or wrong about it, in other words, if Z happens instead of Y, it does not matter one bit; that gives us invaluable information about the next steps that can be taken.  Moreover, a hypothesis allow us to test our guesses.

On the other hand, there is a trend called Data Driven-Science, which is exactly what it sounds like.  Due to the power of computers and bioinformatics, we can collect and organize data at rates much higher than was ever possible. This is a good thing, do not get me wrong; as we keep elucidating the wonderful complexity of biology, we realize how many molecular interactions are possible in a given organism.  This is complex enough to keep us entertained for a while, but for that we need serious computer power.

Precisely because of this huge amount of available data, we must be very aware that we are walking a very fine line here.  We are in danger of losing sight of the whole biological picture while we are looking at all the shiny objects whose names end in “-ome” or -“omics”.  As far as I know, this is a phenomenon exclusive of the life sciences because of the quite overwhelming amount of data available.  Therefore, there is a lot of data, but sometimes no hypothesis or prediction or even any inkling of thought.

The fad seem to have started with the genome and its offspring, genomics.  One definition of a genome is the compendium of all the genes in an organism.  Genomics is the study of genomes. A similar relationship exists between a proteome and proteomics, between a glycome and glycomics (sugars) and between a lipidome and lipidomics (fats).  These are only examples.  There are many more.

Many people hailed the sequencing of a human genome (note that I am not saying the human genome) as the pinnacle of scientific discovery.  It was great indeed, but what some people did not realize is that sequencing was not the end of the story.  The next step was to figure out how all those gene products, as well as the many DNA sequences that did not code for any genes worked together.  This objectively is being aggressively pursued nowadays.

Now, here’s the thing; in a very simplified way, we can safely say that in a living cell, genes code for proteins, proteins can interact with lipids, sugars and nucleic acids.  Just to give you an example, there is a class of proteins called histones, which are closely related to DNA both physically as well as physiologically.  In fact, all of these macromolecules, proteins, nucleic acids, carbohydrates, etc., can and do interact with each other.  Otherwise, there is no life.

Now, didn’t the study of all that used to be called biochemistry?  And do not even get me started on “the” connectome!

Now, I am not saying that these new classification schemes are wrong or useless, far from that.  My point is that these are very useful as long as we keep in mind that all of these aspects are part of an integrated reality.  The thing is that most scientist do realize this; it is when we try to report and explain these results to the public that it can get confusing.

That said, do you want to know why this trend amuses me (when it does not irritate me)?

NO?  Well, I’m telling you anyway…

At the dawn of molecular biology, in the 1950s, many of the pioneers in this field dismissed in a rather impolite way the classical aspects of biology like taxonomy for example, calling it mere “stamp collecting”, not science (look up Edward O. Wilson vs. James D Watson as an example; BTW, Watson is not strange to say, ‘controversial’ statements).  In this sense, these “hot-shot” molecular biologists echoed the sayings of one of Physics’ greats, Ernest Rutherford.  Another Ernest (Ernst Mayr, one of biology’s greats) intelligently rebutted Rutherford’s argument, but I digress.

You know what? All this “-omes” and -“omics” business (“as is”, when not integrated in a coherent way) seems to me awfully like a classifying scheme pretty similar to stamp collecting…

Once again, as frequently happens in science, we’ve come full circle.  I love it!

Stamp collecting, by the way, is a great, educational hobby.

(:-)

If you want to know more

http://lhncbc.nlm.nih.gov/lhc/docs/published/2001/pub2001047.pdf

http://www.sciencemag.org/content/216/4547/718.extract

(The links above are especially insightful commentaries)

Other informative links:

http://www.genome-engineering.com/from-hypothesis-to-data-driven-research.html

http://www.ncbi.nlm.nih.gov/pubmed/14696046

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7 Comments

  1. It’s not just the life sciences. I’m too lazy to look it up at the moment, but there is a move to do the same thing with history in order to discern if there are predictable cycles in social upheaval, violence, innovation and such. They are using computers to digest data points involving economics, weather patterns, population density, birth rates and anything else you can think of. One of their preliminary findings has led to the prediction that we are entering into a period of increased unrest and violence which should peak around 2020. It’s highly controversial – and of course runs a huge risk of turning history into a bunch of charts. But I’m very interested to see if they actually find anything. It’s a whole new world out there, eh?

    1. Have you read Asimov’s “Foundation” novels? They depict a society where mathematicians (called psychohistorians) are able to predict the behavior of societies in very much that way. They could predict the probability of revolutions, dictators, etc…. Thanks for the comment!

  2. Great post. The challenge is not to lose sight of the forest for all the trees… testing a hypothesis and seeking understanding is the essence of science. As you point out, collections are useful to that end, but they’re not an end in themselves.

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