Oh, that’s right — that’s what philosophers are good for. They’re really good at questioning models. John Wilkins has been busily dismantling the cheap and easy metaphors we use to describe molecular biological concepts in a series of posts, taking on genes as language, other popular gene myths and metaphors, and explaining why genes aren’t information. The problem is that when we explain stuff we know well to students, we use metaphors and analogies to get across the initial ideas, and unfortunately, because scientists are human, the metaphors take on a life of their own and sometimes become the dominant paradigm for understanding the reality. And that can be hazardous.
I’ve lived through the era in which everyone started thinking of the genome as an elaborate computer program — we still have lots of people thinking that way, and in some ways it’s gotten worse as bioinformatics has brought in a synergy with computer science. But it’s not! It’s nothing like a series of instructions! This model has become a serious impediment to getting the new generation of advanced students to understand the biology, and worse, they try to shoehorn the biology into how they think a sophisticated computer program ought to work.
We’ve also got the problem of naive idiots thinking the metaphor is the thing and drawing false conclusions. The genome is a recipe, and every recipe needs a cook, therefore God, etc., etc., etc., ad nauseam.
Genes and DNA are one important component of a complex of compartmentalized biochemical reactions, in which every reaction product interacts with and influences the state of the whole. We’re seeing an excessive reductionism borne of the last 50 years of success in molecular biology, and it’s about time the pendulum swung back to a more balanced perspective. One gene tells us very little; you need to step back and look at the interactions of networks of gene products in a complex environment to understand what’s going on in the cell, and then you have to step back further to look at patterns of interactions between cells, and then further still to see how individuals interact with one another and the environment, and then you have to step way back to see how populations interact, and then, maybe then, you’re really talking about evolution.