Tag: Linkonomicon

Would you outsource your gel to a gel-informatician?

Sean Eddy explains why sequencing is replacing many older assays, and why biologists need to learn to analyze their own data.

“High throughput sequencing for neuroscience”:

If we were talking about a well-defined resource like a genome sequence, where the problem is an engineering problem, I’m fine with outsourcing or building skilled teams of bioinformaticians. But if you’re a biologist pursuing a hypothesis-driven biological problem, and you’re using using a sequencing-based assay to ask part of your question, generically expecting a bioinformatician in your sequencing core to analyze your data is like handing all your gels over to some guy in the basement who uses a ruler and a lightbox really well.

Data analysis is not generic. To analyze data from a biological assay, you have to understand the question you’re asking, you have to understand the assay itself, and you have to have enough intuition to anticipate problems, recognize interesting anomalies, and design appropriate controls. If we were talking about gels, this would be obvious. You don’t analyze Northerns the same way you analyze Westerns, and you wouldn’t hand both your Westerns and your Northerns over to the generic gel-analyzing person with her ruler in the basement. But somehow this is what many people seem to want to do with bioinformaticians and sequence data.

It is true that sequencing generates a lot of data, and it is currently true that the skills needed to do sequencing data analysis are specialized and in short supply. What I want to tell you, though, is that those data analysis skills are easily acquired by biologists, that they must be acquired by biologists, and that that they will be. We need to rethink how we’re doing bioinformatics.

I would add this: it takes some time to learn, but in the end it’s not that hard, people. Students in chemistry and physics routinely learn the requisite skills. We need to educate biologists who expect to do programming, math, and statistics.

What a cute baby. . .solar system

The folks at Atacama Large Millimeter/Submillimeter Array (ALMA) just released an insanely detailed image of a developing star and the surrounding disc of material that may become its planetary system.

Credit: ALMA (NRAO/ESO/NAOJ); C. Brogan, B. Saxton (NRAO/AUI/NSF)
Credit: ALMA (NRAO/ESO/NAOJ); C. Brogan, B. Saxton (NRAO/AUI/NSF)

Phil Plait explains why this image is more than aesthetically interesting at Slate.

From what we understand of planet formation, a star and disk this young shouldn’t have a planetary system evolved enough to create these gaps. That’s a bit of a shock. Research published in 2008 also indicated the presence of a new planet, and I’ll be curious to see how this new observation fits in with that work as well. – Phil Plait

HT: Amy Shira Teitel

Will the future run out of technology?

If you haven’t seen it, this opinionated, provocative, and forceful essay by Bruce Gibney at Founder’s Fund is a great read. Starting with the question of why venture capital return has generally sucked over the past two decades, he delves into issue of real vs. fake technology, why we’ve been too quick to be satisfied with incremental progress, and whether there is that much revolutionary technology left to invent.

“What happened to the future?”:

Have we reached the end of the line, a sort of technological end of history? Once every last retailer migrates onto the Internet, will that be it? Is the developed world really developed, full stop? Again, it may be helpful to revisit previous conceptions of the future to see if there are any areas where VC might yet profitably invest.

In 1958, Ford introduced the Nucleon, an atom-powered, El Camino-shaped concept car. From the perspective of the present, the Nucleon seems audacious to the point of idiocy, but consider at the time Nautilus, the first atomic submarine, had just been launched in 1954 (and that less than ten years after the first atomic bomb). The Nucleon was ambitious – and a marketing gimmick, to be sure – but it was not entirely out of the realm of reason. Ten years later, in 1968, Arthur C. Clarke predicted imminent commercial space travel and genuine (if erratic) artificial intelligences. “2001: A Space Odyssey” was fiction, of course, but again, its future didn’t seem implausible at the time; the Apollo program was ready to put Armstrong on the moon less than a decade after Gagarin, and computers were becoming common place just a few years after Kilby and Noyce dreamed up the integrated circuit. The future envisioned from the perspective of the 1960s was hard to get to, but not impossible, and people were willing to entertain the idea. We now laugh at the Nucleon and Pan Am to the moon while applauding underpowered hybrid cars and Easyjet, and that’s sad. The future that people in the 1960s hoped to see is still the future we’re waiting for today, half a century later. Instead of Captain Kirk and the USS Enterprise, we got the Priceline Negotiator and a cheap flight to Cabo.

There are major exceptions: as we’ve seen, computers and communication technologies advanced enormously (even if Windows 2000 is a far cry from Hal 9000) and the Internet has evolved into something far more powerful and pervasive than its architects had ever hoped for. But a lot of what seemed futuristic then remains futuristic now, in part because these technologies never received the sustained funding lavished on the electronics industries. Commercializing the technologies that have languished seems as good a place as any to start looking for ideas

Nature on the PhD Glut

This week Nature covers the online response to Eve Marder’s piece in eLife arguing that we shouldn’t shrink PhD programs. The article mentions my response and adds a few more comments by people with different perspectives. Go over and read it, and chime in with your opinions!

Can science fiction cure our innovation starvation?

Over at Pacific Standard this week, I look at Arizona State University’s fascinating Project Hieroglyph – a project to inspire us to think big with science fiction. The project, inspired in part by Neal Stephenson, just put out an excellent anthology of SF edited by Ed Finn and Kathryn Cramer, featuring thought experiments worked out as SF stories.

In the preface to the anthology, Stephenson looks back at the great technological achievements of the mid-20th century, notably the Apollo program, and worries that we are no longer a society that can get big things done. We’re unwilling to think big, attempt truly ground-breaking ideas, or solve society’s biggest problems. We need to unshackle our imaginations, and SF can help us do that.

You can read my response at Pacific Standard, but here’s the tl/dr version:

Scientists and engineers have plenty of imagination. What they don’t always have are the incentives and support to take big intellectual risks. Making the case that we should tackle big ideas that might fail is Project Hieroglyph’s most valuable contribution. Neal Stephenson writes that “the vast and radical innovations of the mid-twentieth century took place in a world that, in retrospect, looks insanely dangerous and unstable.” Pursuing insanely dangerous ideas—like nuclear weapons—is probably not the best way to build a better society. But risking failure is critical in science and technology. Unfortunately, failure is expensive, and the lack of money is probably the best explanation for why our society isn’t “executing the big stuff” that Stephenson wants to see. Scientists facing increasingly poor career prospects become risk-averse. Venture capitalists who complain that they only have 140 characters instead of flying cars are nevertheless hesitant to fund the expensive and risky development of technology that could be genuinely transformative. We certainly need imagination in science, and we should tell inspiring stories about big ideas. But to realize those ideas, we have to pay for them.

Thoughts?