There’s a certain kind of headline I have become sick of: “Scientists Have Sequenced the Genome of Species X!”

Fifteen years ago, things were different. In 1995, scientists published the first complete genome of a free-living organisms ever–that of a nasty germ called Haemophilus influenzae. Bear in mind, this was in the dark ages of the twentieth century, when a scientist might spend a decade trying to decipher the sequence of a single gene.

And then, with a giant thwomp, a team of scientists dropped not just one gene, but 1740 genes, spelled out across 1.8 million base pairs of DNA. At the core of the paper was an image of the entire genome, a kaleidoscopic wheel marking all the genes that it takes to be H. influenzae. It had a hypnotizing effect, like a genomic mandala. Looking at it, you knew that biology would never be the same.

Looking over that paper today, I’m struck by what a catalog it is. The authors listed every gene and sorted them by their likely function. They didn’t find a lot of big surprises about H. influenzae itself. It had genes for metabolism, they reported, and genes for attaching to host cells, and for sensing the environment. But scientists already knew that. What was remarkable was the simple fact that scientists could now sequence so much DNA in so little time.

Then came more microbes. Then, ten years ago this coming June, came a rough draft of the human genome. Then finished drafts of other animals: chickens, mice, flies, worms. Flowers, truffles, and malaria-causing parasites. They came faster and faster, cheaper and cheaper. The acceleration now means that the simple accomplishment of sequencing a genome is no longer news.

On Wednesday I caught a talk at Yale by Jonathan Rothberg, a scientist who invented “next-generation sequencing” in 2005. By sequencing vast numbers of DNA fragments at once, the new technology made it possible to get a genome’s sequence far faster than earlier methods. Rothberg’s company, 454, got bought up by Roche, leaving him without a lot to do. So he came up with a new machine: a genome sequencer about the size of a desktop printer that can knock out complete genomes with high accuracy in a matter of hours. Rothberg has been unveiling details of the machine over the past few weeks. To convince his audience that the machine actually works, he flashed another mandala wheel–the 4.7 million base pairs of E. coli.

I recalled when the first E. coli genome was published in 1997. It was the result of years of work by 17 co-authors, an event celebrated in newspapers. Now Rothberg just threw up a quick slide of the germ’s genome just to show what he could do in a matter of hours. And I have to say that the sight of yet another circular map of a genome, on its own, no longer gave me a thrill. It’s a bit like someone waving you over to a telescope and saying, “Look! I found a star!”

What remains truly exciting is the kind of research starts after the genomes are sequenced: discovering what genes do, mapping out the networks in which genes cooperate, and reconstructing the deep history of life. Thanks to the hundreds of genomes of microbes scientists can now compare, for example, they can see how the history of life is, in some ways, more like a web than a tree. Insights like these are newsworthy. The sequencing of those genomes, on its own, is not.

And yet my email inbox still gets overwhelmed with press releases about the next new genome sequence. The press releases typically read like this:

“Scientists have sequenced the genome of species X. Their research, published today in the Journal of Terribly Important Studies, will lead to new insights about this important species. Maybe it will even cure cancer or eliminate world hunger!”

And then those press releases give rise to news articles. Here are dozens of pieces that came out over the past couple days, describing the freshly-sequenced genome of the zebra finch. What did the scientists actually learn about zebra finches through this exercise? The articles typically referred to 800 genes involved in the birds learning how to sing. Of course, nobody seriously would expect them to use just one or two genes for something so complex, so this was no big surprise. The articles also mentioned that a lot of the genes were similar to human language genes. This is not really news, either. For the most part, the articles look to the future–to experiments that scientists will be able to do on zebra finches, in the hopes of learning about human speech. But that’s not news of an achievement–that’s a promise.

Perhaps press release writers and journalists are still operating on the assumption that any new genome is news. But that assumption has been wrong for years now. Let’s wait to see what scientists actually discover in those marvelous mandalas.

[Update: Thanks to Jonathan Eisen for coining the easy-t0-remember acronym for my current disorder: YAGS. That goes into my personal lexicon right away.]

Henry Edward Roberts didn’t set out to kick-start the computer revolution. He was just trying to get out of debt.

Roberts, who died yesterday at 68, was an Air Force man in his younger days and a medical doctor in his later ones, but it was the middle part of his life that changed the world. In the mid-1970s, Roberts started a company call Micro Instrumentation and Telemetry Systems (MITS), and in 1975 introduced the Altair 8800—one of the first computers available and affordable for home hobbyists.

When Popular Electronics magazine featured him and the computer on its cover, it caught the attention of two young computer-philes, Bill Gates and Paul Allen. Gates and Allen quickly reached out to Roberts, looking to create software for the Altair. Landing a meeting, the pair headed to Albuquerque, N.M., where Roberts’ company was located. The two went on to set up Microsoft, which had its first offices in Albuquerque [CNET].

When Roberts founded MITS, he was using his technological know-how to make calculators. But when companies like Texas Instruments began to dominate that market, Roberts got squeezed out. In the mid-1970’s, with the firm struggling with debt, Dr Roberts began to develop a computer kit for hobbyists. The result was the Altair 8800, a machine operated by switches and with no display [BBC News]. Prior to the Altair, most computers were still giant machines in university labs, but Roberts said he believed there were enough tech nerds like him in the world that a personal computer—even one as rudimentary as the 8800—would be a success.

Gates reportedly visited Roberts at the hospital days before he died, and Gates and Allen paid tribute to their mentor in a statement. “Ed was willing to take a chance on us–two young guys interested in computers long before they were commonplace–and we have always been grateful to him,” Gates and Allen said. “The day our first untested software worked on his Altair was the start of a lot of great things” [CNET].

Roberts sold off his company in 1977 and retired to farming before becoming an internist. However, his son David Roberts says, he remained interested to the last in his accidental revolution. He never lost his interest in modern technology, even asking about Apple’s highly anticipated iPad from his sick bed. “He was interested to see one,” said Roberts, who called his father “a true renaissance man” [AFP].

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Image: DigiBarn Computer Museum

Imagine that you’re in a game show and your host shows you three doors. Behind one of them is a shiny car and behind the others are far less lustrous goats. You pick one of the doors and get whatever lies within. After making your choice, your host opens one of the other two doors, which inevitably reveals a goat. He then asks you if you want to stick with your original pick, or swap to the other remaining door. What do you do?

Most people think that it doesn’t make a difference and they tend to stick with their first pick. With two doors left, you should have even odds of selecting the one with the car. If you agree with this reasoning, then you have just fallen foul of one of the most infamous of mathematical problems – the Monty Hall Dilemma. In reality, you should actually swap every time – doing so means double the odds of getting the car. I will explain why shortly but if you’re currently confused, you are not alone. Over the years, the problem has ensnared countless people, including professional mathematicians. But not, it seems, pigeons.

Walter Hebranson and Julia Schroder showed that, after some training, the humble pigeon can learn the best tactic for the Monty Hall Problem, switching from their initial choice almost every time. Amazingly, humans who get similar extensive practice never develop the optimal strategies that the pigeons pick up. This doesn’t mean that pigeons are “smarter than humans” as some news stories have claimed, but it does mean that the two species approach probability problems in different ways. We suffer because we overthink the problem.

The Monty Hall Dilemma takes its name from Monty Hall, the presenter of a show called Let’s Make a Deal, which involved similar choices. The dilemma became truly legendary when it featured in a column called Ask Marilyn in Parade magazine. When columnist Marilyn vos Savant, the then holder of the Guinness World Record for highest IQ, wrote the correct solution, she was inundated with complaints.

Around 10,000 readers disagreed with her, and wrote in to say as much (these were the days when trolls had to actually pay for postage; read the last letter in particular). Many of them had PhDs and many were mathematicians. Even Paul Erdos, the most prolific mathematician in history, refused to believe this explanation until computer simulations proved beyond all doubt that always switching was the best strategy.

The problem is that most people assume that with two doors left, the odds of a car lying behind each one are 50/50. But that’s not the case – the actions of the host beforehand have shifted the odds, and engineered it so that the chosen door is half as likely to hide the car.

At the very start, the contestant has a one in three chance of picking the right door. If that’s the case, they should stick. They also have a two in three chance of picking a goat door. In these situations, the host, not wanting to reveal the car, will always pick the other goat door. The final door hides the car, so the contestant should swap. This means that there are two trials when the contestant should swap for every one trial when they should stick. The best strategy is to always swap – that way they have a two in three chance of driving off, happy and goatless.

All over the world, people are spectacularly bad at this. We almost always stick or, at best, show indifference. Hebranson and Schroder wanted to see if other species would be similarly vexed. They worked with six Silver King pigeons and altered the game show format to suit their beaks.

Each pigeon was faced with three lit keys, one of which could be pecked for food. At the first peck, all three keys switched off and after a second, two came back on including the bird’s first choice. The computer, playing the part of Monty Hall, had selected one of the unpecked keys to deactivate. If the pigeon pecked the right key of the remaining two, it earned some grain. On the first day of testing, the pigeons switched on just a third of the trials. But after a month, all six birds switched almost every time, earning virtually the maximum grainy reward.

Every tasty reward would reinforce the pigeon’s behaviour, so if it got a meal twice as often when it switched, you’d expect it to soon learn to switch. Hebranson and Schroder demonstrated this with a cunning variant of the Monty Hall Dilemma, where the best strategy would be to stick every time. With these altered probabilities, the pigeons eventually learned the topsy-turvy tactic.

It may seem obvious that one should choose the strategy that would yield the most frequent rewards and even the dimmest pigeon should pick up the right tactic after a month of training. But try telling that to students. Hebranson and Schroder presented 13 students with a similar set-up to the pigeons. There were limited instructions and no framing storyline – just three lit keys and a goal to earn as many points as possible. They had to work out what was going on through trial and error and they had 200 goes at guessing the right key over the course of a month.

At first, they were equally likely to switch or stay. By the final trial, they were still only switching on two thirds of the trials. They had edged towards the right strategy but they were a long way from the ideal approach of the pigeons. And by the end of the study, they were showing no signs of further improvement.

Why is the Monty Hall Dilemma so perplexing to humans, when mere pigeons seem to cope with it? Hebranson and Schroder think this is a case of our own vaunted intelligence working against us. When faced with a problem like this, we try to think it through, working out the best solution before we do anything. This would be fine, except we’re really quite bad at problems involving conditional probability (such as “if this happens, what are the odds of that happening?”). Despite our best attempts at reasoning, most of us arrive at the wrong answer.

Pigeons, on the other hand, rely on experience to work out probabilities. They have a go, and they choose the strategy that seems to be paying off best. They also seem immune to a quirk of ours called “probability matching”. If the odds of winning by switching are two in three, we’ll switch on two out of three occasions, even though that’s a worse strategy than always switching. This is, of course, exactly what the students in Hebranson and Schroder’s experiments did. The pigeons, on the other hand, always switched – no probability matching for them.

In short, pigeons succeed because they don’t over-think the problem. It’s telling that among humans, it’s the youngest students who do best at this puzzle. Eighth graders are actually more likely to work out the benefits of switching than older and supposedly wiser university students. Education, it seems, actually worsens our performance at the Monty Hall Dilemma.

Reference: Journal of Comparative Psychology http://dx.doi.org/10.1037/a0017703

More on bird brains:

• Confirming Aesop – rooks use stones to raise the level of water in a pitcher
• Clever New Caledonian crows use one tool to acquire another
• Bird-brained jays can plan for the future
• Sparrows solve problems more quickly in larger groups
• City mockingbirds can tell the difference between individual people

A little while back I posted a dramatic satellite image of the Soufrière Hills volcano on Montserrat erupting (thumbnail on the right; click to get the embiggened shot).

Well, as from above, so it is from the side as well. Canadian tourist Mary Jo Penkala was on a plane near Montserrat at the time, and after the pilot made an announcement for passengers to look out the port window, she snapped this:

Wow! I’ve seen a lot of amazing things out my airplane window, but never anything close to this. Ms. Penkala is enjoying a bit of well-deserved notoriety for the picture. It’s amazing in and of itself, but I love how we now can get so many views of volcanic plumes: from below, the side, and even from space. These natural disasters cause a huge amount of damage and grief, of course, but the good news is that with enough study we can learn more about them, how to predict them, and when is the best time to get people out of any potentially dangerous regions.