Truth and Beauty
Paul Krugman’s recent NYTimes Magazine article, “How Did Economists Get It So Wrong?” starts with criticizing economists for confusing beauty for truth in the simplified mathematical models of market economies. I’ve been thinking a lot about “beauty” and “elegance” in science since overhearing a discussion of synthetic biology where someone said that it would be possible for scientists to come up with a more “elegant” solution to biological information processing than already exists in evolved living systems.
In science (particularly physics), elegance is defined as mathematical simplicity. Here’s a fun TED talk by Murray Gell-Mann all about it beauty and truth in physics:
I think that systems biology is driven by a similar underlying principle; the idea that there is an underlying beauty to living systems that can be explained by simple, beautiful equations. Synthetic biology has been described as the “electrical engineering” to systems biology’s “physics” and I think it’s mainly for this reason. Synthetic biology aims to take the “fundamentals” from systems biology and turn them into an engineering discipline, where the simple equations that govern living systems can be used to design new ones.
Unfortunately, I think the notion that there is underlying simplicity in biological systems is flawed. This is demonstrated best in the work of that most famous physicist turned biologist, Francis Crick. Crick discovered the “central dogma of molecular biology,” a beautifully simple description of how heredity works, where DNA can replicate itself, is transcribed into RNA, which can then be translated into proteins that make up the functions of living cells.
His discovery was tremendous, but in the decades since Crick coined the phrase, the uni-directional, dogmatic simplicity has turned into a chaotic jumble. RNA can make DNA, RNA can act like some proteins, proteins can alter how genes are expressed and how RNAs are processed and more, and there are likely many more complicating factors that have yet to be discovered. In a way, it’s still beautiful, but it’s definitely not simple, and all of these complexities definitely make synthetic biology very challenging, but also fascinating in terms of what we can learn. By trying to understand why even the most successful synthetic biological systems fail to behave exactly as predicted, we may be able to more deeply understand the complexity inherent in biological systems and realize that stripping it away is counterproductive. We’re lucky that so far the failure of oversimplified biological models, unlike the consequences of sticking to oversimplified economic models, only really hurts the graduate students working on the project.
