None, That's a Hardware Problem.

Yuri Lazebnik presents a compelling case for a new mathematical formalism in biology in his fascinating essay “Can a Biologist Fix a Radio? — or, What I Learned while Studying Apoptosis” [pdf]. But I can't shake the sinking feeling that his parable applies equally well to some areas of computer science.

At some point, David said, the field reaches a stage at which models, that seemed so complete, fall apart, predictions that were considered so obvious are found to be wrong, and attempts to develop wonder drugs largely fail. This stage is characterized by a sense of frustration at the complexity of the process, and by a sinking feeling that despite all that intense digging the promised cure-all may not materialize. In other words, the field hits the wall, even though the intensity of research remains unabated for a while, resulting in thousands of publications, many of which are contradictory or largely descriptive. [...]

I hope that it is only a question of time before a user-friendly and flexible formal language will be taught to biology students, as it is taught to engineers, as a basic requirement for their future studies. My advice to experimental biologists is to be prepared.

[via Improbable Research]

Comments

Thanks for the link to that article. It was a good article.

"But I can't shake the sinking feeling that his parable applies equally well to some areas of computer science."

What areas of computer science are like that?

[Mitch]

1) I enjoyed this: "... understanding the system without formal analytical tools requires geniuses, who are so rare even outside biology."

3) I'd like to know what the author thinks are the appropriate formalisms might be. The article is very convincing that "something must be done" and we must "be prepared", but I fear that after finishing the article, no one will have any idea in what way to implement that.

2) I think a more parallel analogy (of the broken radio) would be to software maintenance, where the behavior of components are well-known, but the interaction can be opaque.