“Hey Anna?” he called out.

“Yes?” She reappeared in the doorway.

“I know one of the guys on this jacket. The P.I. is a guy from Caltech, but the real work is by one of his students.”

“Yes?” This was a typical situation, a younger scientist using the prestige of his or her advisor to advance a project.

“Well, I know the student. I was the outside member on his dissertation committee, a few years ago.”

“That wouldn’t be enough to be a conflict.”

Frank nodded as he read on. “But he’s also been working on a temporary contract at Torrey Pines Generique, which is a company in San Diego that I helped start.”

“Ah. Do you still have any financial stake in it?”

“No. Well, my stocks are in a blind trust for the year I’m here, so I can’t be positive, but I don’t think so.”

“But you’re not on the board, or a consultant?”

“No no. And it looks like his contract there was due to be over about now anyway.”

“That’s fine, then. Go for it.”

No part of the scientific community could afford to be too picky about conflicts of interest. If they were, they’d never find anyone free to peer-review anything; hyperspecialization made every field so small that within them, everyone seemed to know everyone. Because of that, so long as there were no current financial or institutional ties with a person, it was considered okay to proceed to evaluate their work in the various peer-review systems.

But Frank had wanted to make sure. Yann Pierzinski had been a very sharp young biomathematician he was one of those doctoral students whom one watched with the near certainty that one would hear from them again later in their career. Now here he was, with something Frank was particularly interested in.

“Okay,” he said now to Anna. “I’ll put it in the hopper.” He closed the file and turned as if to check out something else.

After Anna was gone, he pulled the jacket back up. “Mathematical and Algorithmic Analysis of Palindromic Codons as Predictors of a Gene’s Protein Expression.” A proposal to fund continuing work on an algorithm for predicting which proteins any given gene would express.

Very interesting. This was an assault on one of the fundamental mysteries, an unknown step in biology that presented a considerable blockage to any robust biotechnology. The three billion base pairs of the human genome encoded along their way some hundred thousand genes; and most of these genes contained instructions for the assembly of one or more proteins, the basic building blocks of organic chemistry and life itself. But which genes expressed which proteins, and how exactly they did it, and why certain genes would create more than one protein, or different proteins in different circumstances all these matters were very poorly understood, or completely mysterious. This ignorance made much of biotechnology an endless and very expensive matter of trial and error. A key to any part of the mystery could be very valuable.

Frank scrolled down the pages of the application with practiced speed. Yann Pierzinski, Ph.D. in biomath, Caltech. Still doing postdoc work with his thesis advisor there, a man Frank had come to consider a bit of a credit hog, if not worse. It was interesting, then, that Pierzinski had gone down to Torrey Pines to work on a temporary contract, for a bioinformatics researcher whom Frank didn’t know. Perhaps that had been a bid to escape the advisor. But now he was back.

Frank dug into the substantive part of the proposal. The algorithm set was one Pierzinski had been working on even back in his dissertation. Chemical mechanics of protein creation as a sort of natural algorithm, in effect. Frank considered the idea, operation by operation. This was his real expertise; this was what had interested him from childhood, when the puzzles solved had been simple ciphers. He had always loved this work, and now perhaps more than ever, offering as it did a complete escape from consciousness of himself. Why he might want to make that escape remained moot; howsoever it might be, when he came back he felt refreshed, as if finally he had been in a good place.

He also liked to see patterns emerge from the apparent randomness of the world. This was why he had recently taken such an interest in sociobiology; he had hoped there might be algorithms to be found there which would crack the code of human behavior. So far that quest had not been very satisfactory, mostly because so little in human behavior was susceptible to a controlled experiment, so no theory could even be tested. That was a shame. He badly wanted some clarification in that realm.

At the level of the four chemicals of the genome, however in the long dance of cytosine, adenine, guanine, and thymine much more seemed to be amenable to mathematical explanation and experiment, with results that could be conveyed to other scientists, and put to use. One could test Pierzinski’s ideas, in other words, and find out if they worked.

He came out of this trance of thought hungry, and with a full bladder. He felt quite sure there was some real potential in the work. And that was giving him some ideas.

He got up stiffly, went to the bathroom, came back. It was midafternoon already. If he left soon he would be able to hack through the traffic to his apartment, eat quickly, then go out to Great Falls. By then the day’s blanching heat would have started to subside, and the river’s gorge walls would be nearly empty of climbers. He could climb until well past sunset, and do some more thinking about this algorithm, out where he thought best these days, on the hard old schist walls of the only place in the Washington D.C. area where a scrap of nature had survived.

Mathematics sometimes seems like a universe of its own. But it comes to us as part of the brain’s engagement with the world, and appears to be part of the world, its structure or recipe.

Over historical time humanity has explored farther and farther into the various realms of mathematics, in a cumulative and collective process, an ongoing conversation between the species and reality. The discovery of the calculus. The invention of formal arithmetic and symbolic logic, both mathematicizing the instinctive strategies of human reason, making them as distinct and solid as geometric proofs. The attempt to make the entire system contained and self-consistent. The invention of set theory, and the finessing of the various paradoxes engendered by considering sets as members of themselves. The discovery of the incompletability of all systems. The step-by-step mechanics of programming new calculating machines. All this resulted in an amalgam of math and logic, the symbols and methods drawn from both realms, combining in the often long and complicated operations that we call algorithms.

In the time of the development of the algorithm, we also made discoveries in the real world: the double helix within our cells. DNA. Within half a century the whole genome was read, base pair by base pair. Three billion base pairs, parts of which are called genes, and serve as instruction packets for protein creation.

But despite the fully explicated genome, the details of its expression and growth are still very mysterious. Spiraling pairs of cytosine, guanine, adenine, and thymine: we know these are instructions for growth, for the development of life, all coded in sequences of paired elements. We know the elements; we see the organisms. The code between them remains to be learned.

Mathematics continues to develop under the momentum of its own internal logic, seemingly independent of everything else. But several times in the past, purely mathematical developments have later proved to be powerfully descriptive of operations in nature that were either unknown or unexplainable at the time the math was being developed. This is a strange fact, calling into question all that we think we know about the relationship between math and reality, the mind and the cosmos.