31–40 of 62 posts
Poets say science takes away from the beauty of the stars - mere globs of gas atoms. I too can see the stars on a desert night, and feel them. But do I see less or more?
This article was fascinating to read. The deep understanding in genetics, biology, engineering, etc..., and all the work from thousands of people that ultimately culminated in the production of this vaccine, illustrates how beautiful science is.
Since the sequence is available, does this mean I could pool some money with some friends and buy a dna sequencer and start printing my own vaccine?
The futurologist in me imagines prescriptions containing RNA sequences which you get to the nearest pharmacy to 3D print the drug. Future of the medicine looks more exciting than ever.
Great post! A non-technical detail that the post misses is the human story here. Katalin Kariko, the biochemist that pioneered the idea of delivering vaccines in mRNA form, got nothing but rejections for her grant applications for this very idea and was eventually demoted from tenure track at U Penn. Whatever you think of this, it's a misleading understatement to describe it as: > As with other fundamental scientific…
While not an entirely false picture, the real situation is far from that clear and scientific struggles of Katalin Karikó, who finally left the academia for private sector (she is now a vice president in BioNTech, one of the vaccine-producing corporations) is an illustration of the perils of the contemporary grant systems.
Truly revolutionary concepts are often indistingushable from bullshit. At least from the grant committee point of view. Your best chance to snap up a grant is to come with a project of marginal improvement that produces one or two papers in a reliable timeframe.
Marginal improvements have their indisputable value, but they mostly appeal to risk-averse people; whoever wants to work on something really outlandish, must rely on other sources of financing, often private. After all, there is a risk of utter failure = not producing even that one paper that is, these days, a basic unit of wealth in the Publish-or-Perish world. Or of a delay that breaks the original time plan.
Any suggestions where I could go to learn more specifically about this sort of genetic engineering and more generally about biology (University level and above).
Nice article. There are more interesting things to say about RNA that makes it a bit less like code - for example that it too can fold to a 3d structure, with some cases that can cause problems - hairpins for example where the sequence is palindrome-like (in the complementing letters) ACG followed by CGU can fold onto itself. This caused the problems with the initial batch of CDC's PCR tests
Nice article. There are more interesting things to say about RNA that makes it a bit less like code - for example that it too can fold to a 3d structure, with some cases that can cause problems - hairpins for example where the sequence is palindrome-like (in the complementing letters) ACG followed by CGU can fold onto itself. This caused the problems with the initial batch of CDC's PCR tests
as I understood it from the "universal table for mapping RNA codons to amino acids" one can encode the same information differently. So is it just possible define the information you want to encode and use a computer to calculate the correct encoding so that things don't get tangled up?
Earlier quoted context omitted.
Kudos for the fascinating article. Since you mentioned security, and the well known trick of sending an ambiguous message that is interpreted differently by different interpreters, I wonder what you might think of enlisting the hackers of the world to help in viral research. Seems as though adversarial thinking skills could come in handy?
I definitely think the computing / information security mindset is relevant and applicable to computational biology. There are sadly structural reasons why the crossover is very hard. I spent 18 months at a university doing this kind of research but it is not a natural fit. Also, I do have to tell you, I spent 10 years studying this stuff before I became useful to the field. So you don't just jump in there :-)
I would be happy to devote 10 years (or a lifetime for that matter) to bring the fields to bear on one another, sounds super interesting.
As others have already noted, most work at the "intersection" of the domains is currently superficial, say designing support software as opposed to actually hacking on the genetic code.
Could you go into more detail about the structural reasons that prevent a clean mapping? Can you think of ways to lower the barrier so as to engage more people? Do you see problems that are relatively easy to export?
An example of exporting problems, in this case from digital pathology, is the Camelyon challenge, which brought machine learning to bear on cancer detection. Hype aside, the important aspect is that researchers working to segment images and train neural networks did not have to have a biochemistry background, nor understand cellular functions and provenance, nor understand staining protocols. A clean export.
I am basically looking for a "biocrackme" that is relatively self contained.