11–20 of 37 posts
Can I give you my genome? Or will I be able to reproduce your methods from this site?
This is a course on a fairly novel field of research, not a method to do anything remotely consumer-facing.
> Learning the DNA regulatory code of the genome This is so interesting. I cannot imagine what kind of language evolution chose to build on top of DNA. There must be some paradigm it maps to, and it's going to be incredibly interesting to see if a compiler/interpreter can be made for DNA, along with higher level languages that compile down to it.
DNA also contains regulatory segments, errors, “dead” code left over (and carried through generations) long after it stopped being transcribed, DNA once inserted by viruses (both active and inactive) etc etc...
If you want an analogy with computer code: it’s most like a spaghetti-code hair ball of assembly coding it’s own compiler, IDE, vim, a few games, and a neural network ten magnitudes the size of anything tensorflow can do. It does it all on hardware that works only probabilistically. And it is constantly starved for resources, leading to hacks such as DNA sequences that code for two completely different functioning proteins depending on reading it either forward or backward, or starting to read at an offset (what’s called a “reading frame”).
There’s a thick book on molecular biology by Alberts et al. It’s the most phantastic deep dive into this, any many other, insanities. I believe Larry Page used to recommend it to all new googlers.
> Learning the DNA regulatory code of the genome This is so interesting. I cannot imagine what kind of language evolution chose to build on top of DNA. There must be some paradigm it maps to, and it's going to be incredibly interesting to see if a compiler/interpreter can be made for DNA, along with higher level languages that compile down to it.
If you’re interested, much of what you’re asking about is actually known: (some) DNA sequences map directly to protein sequences. Because DNA has a 4 letter alphabet (G, C, T, A), it takes three to map to one of the 2x different amino acids that make up proteins. Proteins, in turn, are the “machines” that work in cells. DNA also contains regulatory segments, errors, “dead” code left over (and carried through generati…
https://www.amazon.com/Molecular-Biology-Cell-Bruce-Alberts/...
It's standard reading at the very least as intro grad/senior undergrad student in the biosciences.
Great book, well written, well curated.
Parent commenter is correct, DNA->function is massively complicated. The main wiki article to start with is:
https://en.wikipedia.org/wiki/Central_dogma_of_molecular_bio...
As the article notes, there are endless exceptions and edge cases. It links to various examples of those.
> Learning the DNA regulatory code of the genome This is so interesting. I cannot imagine what kind of language evolution chose to build on top of DNA. There must be some paradigm it maps to, and it's going to be incredibly interesting to see if a compiler/interpreter can be made for DNA, along with higher level languages that compile down to it.
Now, programmers, by our neurophysiology and training recognize things that look like abstractions in what evolution produces, and near-abstractions are useful to reduce our cognitive load when we're studying biology, but a biologist always keeps in mind a list of exceptions to those abstractions in mind. If you don't know of exceptions, it is almost always a fruitful research question to find them.
> Learning the DNA regulatory code of the genome This is so interesting. I cannot imagine what kind of language evolution chose to build on top of DNA. There must be some paradigm it maps to, and it's going to be incredibly interesting to see if a compiler/interpreter can be made for DNA, along with higher level languages that compile down to it.
This is a common idea among computer scientists looking at biology. They see "sequence of base pairs" and immediately think of a Turing machine's tape or a memory segment in a computer. It leads them astray. There's no reason to think that evolution has or would construct anything resembling a language or a language paradigm. Evolution doesn't introduce abstractions. Now, programmers, by our neurophysiology and train…
https://www.damninteresting.com/on-the-origin-of-circuits/
tl;dr - evolution takes advantage of the entire solution space without any respect the the abstraction layers we've created in our minds.
If of interest, other notes are available at cs522.stanford.edu and more will be available shortly!
Any chance the course has room for the other side of the coin? Namely, how neuroevolution and genetic strategies inform deep reinforcement learning?
Am also interested in learning about the state-of-the-art in cloud based packages. I noticed recently Google released a tool called DeepVariant for use on their genomics platform.
https://github.com/google/deepvariant
Creating a universal SNP and small indel variant caller with deep neural networks
This may sound like a naive approach, but is there anything special hindering us from building such a simulator or is it just that scientists will not find it useful as it will take too long before we know which nucleotides are important for our goals?
> Learning the DNA regulatory code of the genome This is so interesting. I cannot imagine what kind of language evolution chose to build on top of DNA. There must be some paradigm it maps to, and it's going to be incredibly interesting to see if a compiler/interpreter can be made for DNA, along with higher level languages that compile down to it.
If you’re interested, much of what you’re asking about is actually known: (some) DNA sequences map directly to protein sequences. Because DNA has a 4 letter alphabet (G, C, T, A), it takes three to map to one of the 2x different amino acids that make up proteins. Proteins, in turn, are the “machines” that work in cells. DNA also contains regulatory segments, errors, “dead” code left over (and carried through generati…
Not that I have a book to recommend instead...
Anybody knows why we cant just write a cell simulator and start experimenting that way with DNA manipulation? I mean I have no idea what the first nucleotides are for, but when I have a simulator I can try changing them and see what happens? This may sound like a naive approach, but is there anything special hindering us from building such a simulator or is it just that scientists will not find it useful as it will t…
This is hard. To my knowledge we can't even write most basic components of a cell simulator yet. One of the obvious requirements would be a protein folding simulator. Nobody has been able to come up with a working one of those yet.
> when I have a simulator I can try changing them and see what happens?
If you write a simulator that does this you will be a billionaire and probably win a Nobel prize in medicine while you're at it.
Earlier quoted context omitted.
This is a course on a fairly novel field of research, not a method to do anything remotely consumer-facing.
I disagree! It's a fantastic domain for startups! Nanopore is readily available. I have sequenced stuff in my kitchen, and I'm a computer scientist.