"omics" + (analysis & in silico) = back to the future

Well, I've been having fun reading John Hawks' posts on the term "genomics," and I'm sure Evolgen thinks I'm a bit too preoccupied with the three old thugs of population genetics...but this article, Marriage of Math and Genetics Forges New Scientific Landscape is kind of funny, the past is the future! After all, both R.A. Fisher and J.B.S. Haldane were trained as mathematicians, and Sewall Wright was a lover who regretted his early lack of experience. Over a year ago PLOS had a article out, Mathematics Is Biology's Next Microscope, Only Better; Biology Is Mathematics' Next Physics, Only Better. Yes, I think the days might be coming to an end when scientists who wanted to avoid math1 pursued biology...but this is where sociology is important. The influx of mathematically passionate individuals into modern biology is essential for the field to take off into new dimensions. Luca Cavalli-Sforza in A Genetic and Cultural Odyssey states that his book Cultural Transmission and Evolution made such a trivial impact on anthropology because the field did not have a critical mass of mathematically fluent individuals to understand the technical details he was presenting.2 Within biology itself most intellectual histories seem to suggest that the original ideas of Fisher, Wright and Haldane were often misunderstood because of the opacity of mathematical technique to most trained biologists. I am skeptical that Leibniz's general algebra is going to arrive on the scene anytime soon, but many of the verbal jousts could, I believe, be obviated by recourse to more precise formalization. Where emotions can find secure purchase on the nooks and irregularities of words...mathematical notation is a more slippery species of beast.

1 - As a friend of mine has noted biology still explores only a small fraction of Hilbert space, fear not!

2 - Cavall-Sforza's contention is debatable, human culture might simply be intractable using the analytic models that he put forward, but do note that it seems likely that the emergence of the Modern neo-Darwinian Synthesis was hindered by the lack of mathematical fluency in much of the biological community.

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The influx of mathematically passionate individuals into modern biology is essential for the field to take off into new dimensions.

Absolutely. It's striking that a lot of the top biologists now-- Eric Lander and Leonid Kruglyak, no name a couple (off the top of my head, with a genetics bias)-- were trained in math/physics before getting into biology. But now, a lot of people trained in biology have a strong math background as well. It's definitely going to to have an effect on the field.

But not knowing math is no impediment. Didn't Mayr learn about Fisher's popgen models through Dobzhansky, who, himself, had limited math knowledge? I guess it could be quite problematic if some mathematical model is propagated through the biology community by people with a poor understanding of math.

Didn't Mayr learn about Fisher's popgen models through Dobzhansky, who, himself, had limited math knowledge

well, according to provine (see sewall wright and evolutionary biology) mayr leaned far more toward wright's ideas because of their congeniality with his own observations in regards to population substructure. and, provine seems to argue that mayr initially garbled the thrust of wright's point, confusing the separate issues of epistatic effects and random genetic drift emerging out of meta-population dynamics. both dobzhansky and mayr seemed to learn toward wright as opposed to fisher because of their intuitions derived from their empirical sense of how important substructure of populations might be as opposed to a genuine understanding of the technical debates between fisher & wright. finally, mayr's verbal models in areas like "genetic revolution" re: speciation can be starting points, but analytic & computational methods seem to be really necessary to supplement the data one can collect empirically.

in any case, most of pop gen is really "baby math," but i would argue that too many people in biology today still don't feel at ease with it....

Hmm. I think that this whole "omics" phenomena has nothing to do with classical population genetics, epidemiology (or molecular genetics) but the scary trend of Big Biology. The NIH wants biologists to think big ... and so some small bench biologists, and other computational biologists have jumped on the bandwagon. It started with Pat Brown and Botstein with their CHIP technology that allowed to analyze the entrire "transcriptome" (the first time "omics" was used outside of genomics). But I think that it's dying out - Big Biology (outside of genome analysis) has not really revolutionized Biology. So yes lots of people are "omics-izing" themselves but it'll die.

most of pop gen is really "baby math," but i would argue that too many people in biology today still don't feel at ease with it....

Baby math can be deceptive. Those problems at the end of the SAT math sections that separate the 800 from 750 people use incredibly simple math, but it's more using math to model. I just started Maynard Smith's Evolutionary Genetics this week -- it's just basic algebra & stats, but unless you were trained as an engineer like he was (or physicist, statistician, etc.), it wouldn't occur to you how to devise the models.

So some might not feel comfortable b/c, although they get established equations & algorithms, they don't feel they're quantitatively imaginative enough to contribute the next equation or algorithm for detecting natural selection. By contrast, some physicists & engineers feel drawn to biology b/c their background isn't indicative of their passion but rather of their quantitative imagination -- once they hit on biology, they get interested and use their quantitative skills to do something they feel more passionate about.

But I think that it's dying out - Big Biology (outside of genome analysis) has not really revolutionized Biology.

I don't know...if you're referring to the trend of calling everything the new "-omics" I'm with you, that will probably fade out.

But microarray technology is the closet thing to a revolution that biology has had in the last 10 years: expression arrays are a powerful way to examine transcription, ChIP-Chip changed how we study DNA-protein interactions, CGH is at least a very useful tool in the study of copy number, and methylation arrays are coming online to change our perspective on epigenetics.

This change in persective can only be described as revolutionary.

I still can't get over in silico.

It kills me every time I see it in a title.
No no, it's not a simulation. It's not a huge computation. It's a reaction run in silico. The dynamics were monitored in silico. Boy that sounds much cooler.

Silly terminology pops into my head all the time, but I just don't have the balls or the flair to go using it.

O well, I guess that's why my next paper is NOT going to be named: "Nanowetting dynamics within novel bio-inspired macromolecular nanoarchitectures monitored in silico."

By beervolcano (not verified) on 27 Mar 2006 #permalink