Synthetic Biology

I read a terrific article written by Michael Specter, published in New Yorker Magazine, entitled "A Life Of Its Own." It asks the question "Where will synthetic biology lead us?"

I'm fascinated by the question. It marries science and ethics in equal measure. I can sympathize with the enthusiastic scientists who envision great benefits - everything from improved health to a way out of our deadly embrace of fossil fuels.

I can't claim to be that kind of scientist. Engineers concern themselves with applying the knowledge that the practitioners of fundamental sciences - physicists, chemists, and mathematicians - unearth for us. We fashion these intellectual raw materials into useful things, and even contribute back what we learn about the fundamentals during process development, but I've been reminded many times that a mechanical engineer is not a physicist. There was a time when I immersed myself into reading biographies of the great physicists of the 20th century. Feynman became a hero of mine after reading his autobiographical short stories in "Surely You're Joking, Mr. Feynman!" and James Gleick's wonderful biography "Genius". I devoured his famous red books, fancying myself a budding physicist.

Then I got my hands on Veltman's "Diagrammatica", and the dream died. It was beyond me. I had neither the physical intuition nor the mathematical chops to see my way through it.

I'm in a worse position with biology. The last biology course that I took came in high school. They taught us the rudiments of DNA, RNA, and the Krebs cycle, but it was well before the polymerase chain reaction came along. Chemistry is not my strong suit either, so the changes that are coming will leave me behind.

Neither of my parents went to college. I was alone when I went off to study mechanical engineering, because neither of them had experienced what I went through.

My youngest daughter is studying biology as an undergraduate now. In spite of all my education, I find myself in a position relative to my daughter similar to what my father had with me. I can relate my experiences as an undergraduate to hers, and tell her what graduate school was like for me. I know enough about fundamentals like thermodynamics, physics, etc. to keep the ball rolling when we talk. But she's already well beyond my capabilities in her chosen field. She's blazing that path alone. She's Lewis and Clark sending letters back to me, Thomas Jefferson, describing the wonders she's experiencing.

I found the New Yorker article particularly interesting, because a number of the phrases evoked things I'd read when the software industry was abandoning older procedural languages like FORTRAN and COBOL and embracing the newer idea of object oriented programming. The problem was complexity: it's impossible to manage all the details that go into developing software when the number of lines of code explode into the hundreds of thousands or millions. Problem solving in general, and computer science in particular, depends on being able to decompose large, intractable problems into smaller, more manageable pieces.

Object oriented programming helps us to manage complexity by mapping software components onto real-world objects and encapsulating the details inside. If done correctly, users of a component need only concern themselves with what they need to provide and what they get back; all the messiness of how it's done is hidden inside.

Brad Cox and others used to talk about "software integrated circuits": each component would have its own well-defined inputs and outputs, much like the pins on a hardware integrated circuit. There would be a marketplace of these software ICs, where you could search for a component that met your needs, plug it in, and off you'd go.

This phrase on page 5 of the article brought that vision back for me: "The BioBricks registry is a physical repository, but it is also an online catalogue. If you want to construct an organism, or engineer it in new ways, you can go to the site as you would one that sells lumber or industrial pipes."

It made me stop and think, because to a great degree the promise of software ICs has not been realized. Writing complex software systems is still a difficult, large scale problem. Object models claiming to model the industry I work in today have not lived up to their promise. The ideal presented by the hardware side of the problem has not translated over to software.

There's still something fundamentally different about software. It's not all science. The irony is that software was distinguished from hardware at the dawning of the computer age because it was believed to be more malleable stuff than the circuits it ran on. You could change it relatively quickly, far more easily than the machine that executed it.

But that's often precisely the problem. It's very easy to change, but the coupling and complexity make it difficult to predict what the effect of the change will be. Brittle software suffers from this problem. The effect of changes in one part of the code often ripple out, resulting in surprising, disappointing, sometimes catastrophic behavior.

Reading about the enthusiasm of biologists made me wonder about the brittleness, coupling, and unintended consequences that face them. Will they have better success than software engineers have to date? And if they do, what lessons can we learn to improve the lot of software development?