21 ms·

Introduction to Genomics for Engineers

310 points by froggychairs 4y ago

lordofgibbons 4y ago
I find the field extremely interesting, but I wish the pay in genomics was better. Compared to fang/unicorn type companies, their pay is way below market and it's really hard to justify the massive pay cut.
- f6v 4y ago
  > their pay is way below market The pay is exactly where market is. There’re ton of wet-lab people wanting to get into “data”. And the industry is less lucrative than showing ads like Google does.
  - nextos 4y ago
    I think Calico (Alphabet) pay is not too far from a SWE at Google. However, this requires a PhD and much more experience.
    - f6v 4y ago
      Just about any “bioinformatics” job requires a PhD in biology-related field. And there’re plenty graduates. That’s the thing, there’s plenty of supply.
      - the_only_law 4y ago
        Yeah but… > This Guide is written specifically by and for computer scientists and engineers. How many engineers already have a bio phd. Who on earth is this actually written for.
qualudeheart 4y ago
Does this touch on recent developments in information biology?
rainmaker124 4y ago
CS person with biology PhD here. The mix of biology and computation is huge, and with the right skill set, interdisciplinary unicorns make tons of money. If you want to see how computation and biology mix, first dive into a standard university Intro Biology course, and then with that foundation, look into computational biology & bioinformatics (they're distinct). You'll find that genomics is only one piece of a much bigger and absolutely fascinating story. To get that basic biology foundation, another post mentioned an EdX Intro Biology course, that would be a terrific start, or just get a recent university-level intro biology textbook. It's not terribly difficult material and you'll be in far better shape than reading a biology-for-laypersons pamphlet.
Exendroinient00 4y ago
Surely sellouts working on ads won't interject the comment section.
- zach_garwood 4y ago
  Wow, those are some sour grapes you got there!
  - Exendroinient00 4y ago
    Almost every thread covering non web/finance fields of software have loads of comments about pay as the first priority derailing entire discussion.
guy4242 4y ago
It's difficult to get into this field if you don't have a graduate degree. I was a double major, Computer Science and Biochemistry, with a minor in Biotechnology. I sent my resume to many biotech and pharma companies, but could not even get an interview. A lot of the jobs said you need 0 years experience if you have a PhD, but 10 years experience if you have a Bachelors. Now that I have 10 years experience as a developer, I've forgotten almost everything I learned in my science education, and I've lost interest.
civilized 4y ago
Really glad to see this, but it reminds me of the earlier HN post that said engineers don't go into genomics because it doesn't pay and requires a lot of investment in learning biology.
- firstplacelast 4y ago
  https://news.ycombinator.com/item?id=33671264 https://news.ycombinator.com/item?id=33671264 ^Most recent discussion I’ve seen. I worked in genomics, left this year because you’re underpaid and often disregarded “IT-help” that assists wildly over-educated and underpaid people driving the actual research in 95% of cases.
  - tetris11 4y ago
    Thats why you stay though, the people are interesting and the work is meaningful and you directly see the fruits of your labors whilst contributing to a codebase that is by default open source.
    - fncivivue7 4y ago
    - deleted 4y ago
      [deleted]
    - firstplacelast 4y ago
      People aren’t anymore interesting than anywhere else. Work is no more meaningful than anywhere else. It’s a big “selling point” for the industry, but it’s just a way to get people to get paid less (yay you’re making the world better than all those garbage people serving coffee or healing sick people or keeping your lights on or optimizing the routes of the goods you have delivered). If you want sustainable systems, trying to be a martyr and work for less only screws this up long term. Code-base is not open-source. It’s biotech R&D, there is zero culture of sharing outside your organization within industry. You can present high-level things at conferences and such, but you’ll have to rip the raw data out of their dead hands…not happening. I’ve been in too many conversations about building software to serve larger groups in this industry. It can happen, but it can’t currently and nobody wants it. Confident someone will find a solution, but everyone wants their own home-grown solutions in their own walled-gardens that no one has access to. Data and the things it can/can’t tell you are held tightly in these companies. I was at a pharma a couple years ago where researchers were explicitly told they COULD NOT test certain compounds in a certain way because they did not want a trace of this data to exist while they were trying to push compounds through the FDA.
penciltwirler 4y ago
Nicee, but I feel like really the only thing you need to know as an eng is DNA -> RNA -> Protein. Sometimes RNA -> DNA via reverse transcriptase. Everything else is just normal Python scripting.
- joshuahedlund 4y ago
  That’s what I thought too until I learned about - the dna that doesn’t code for proteins but makes up the vast majority of human dna - the intron regions of genes that are translated into RNA but then sliced out of the RNA and not transcribed into protein and are 5x larger than the coding parts Those two things alone are absolutely critical to understand to interpret a genome sequence. Of course there is much more.
- greazy 4y ago
  ...no. There is more to genomics than python scripting. This is widely incorrect assumption. A new generation of bioinformaticians and computational biologists are using rust, go, and the web to create, share and deliver. Checkout nextclade.org
- aquafox 4y ago
  You do know that there are things like epigenetics, DNA repair (using specialized proteins), RNAi, post-translational modifications, metabolites (just to name a few)?
- otherme123 4y ago
  Sooner or later you'll have to learn all the other stuff in the linked page: file formats used only in genomics, structural variants, NGS, evolution, regulation, polygenics, etc.
- epgui 4y ago
  I’m a biochemist + software engineer, and while I understand where you’re coming from, IMO that’s a very harmful/self-sabotaging attitude. As soon as you start touching science, everything is important.
- janeway 4y ago
yuppiepuppie 4y ago
Genomics is where I started learning how to program. Having worked as bench scientist in a genetics lab I understood nothing about my lab mates research when they were showing me python scripts of their analysis. Which initially got me curious. Now having been in the in the industry developing apis for large companies for the past 8 years, I’d be keen to get back into it. Any ideas where to start or find jobs in the space? I would love to go back into the space.
- chairhairair 4y ago
  I have a similar story with chemistry. I’d also like to get back into the sciences, but I’m not sure how relevant programmers are.
  - feet 4y ago
    Very relevant and becoming moreso. Check out job postings at research institutes and universities with healthy research departments
    - zelphirkalt 4y ago
      How does one know, whether they are healthy or not?
      - feet 4y ago
        Generally if they are producing consistent, high quality research
dddiaz1 4y ago
I have absolutely loved working in genomics. I am a huge believer that genomics will be a huge part of healthcare in the future, and i have two examples to motivate that point that I think may be interesting to the reader. 1) The Moderna vaccine was made with the help of illumina genome sequencing. They were able to sequence the virus and send that sequence of nucleotides over to moderna for them to develop the vaccine - turning a classically biology problem, into a software problem, reducing the need for them to bring the virus in house. 2) Illumina has a cancer screening test called Galleri, that can identify a bunch of cancers from a blood test. It identifies mutated dna released by cancer cells. This is huge, if we can identify cancer before someone even starts to show symptoms, the chances of having a useful treatment dramatically go up. Disclaimer: I work for illumina, views my own. I wrote some more about why genomics is cool from a technical point of view here (truly big data, hardware accelerated bioinformatics) : https://dddiaz.com/post/genomics-is-cool/ https://dddiaz.com/post/genomics-is-cool/
- pinkwinds 4y ago
  Purposefully blocked for certain countries? "The Amazon CloudFront distribution is configured to block access from your country."
- agumonkey 4y ago
  what kind of math/cs/algorithmic skills do you think one should work on to get a job in this kind of company ?
  - jghn 4y ago
    There are two main flavors of jobs. For one you’ll want to be a phd in something like physics or math. For the other Amy standard software engineering background will do.
- mtlmtlmtlmtl 4y ago
  The thing I'm most excited about long term is biocomputing. Having Turing complete programmatic control over biological systems has an absolutely endless list of transformative applications. Imagine being able to program bacteria that can "infect" the patient and attack tumor cells, or act as fodder to keep autoimmune disease in check. Or let's say we could program stem cells into "liver repair mode" to go and differentiate into new liver cells. Then the implications for things like drug synthesis with the ability to programmatically control enzyme levels to compile more or less arbitrary biosynthetic pathways into fast growing photosynthetic algea, turning CO2, water and sunlight into medicine. It's still a long way off being at that level of applicability, but man oh man it's gonna change everything.
ALittleLight 4y ago
I didn't get this from skimming the first page - but what will this let me do? If I take this course will I be able to mess with a cell or will I just learn some stuff about biology. I saw a recent Lex Friedman podcast where the guest talks about "bioelectric patterns" and somehow getting a worm to grow a second head by messing with those patterns. I would absolutely start on this course now if it was a realistic pathway to doing something like that.
- pgayed 4y ago
  This is the worst outcome of regulation of the life sciences. There is no REPL for the cell. No tinkering allowed. When Marvin Minsky was growing up in New York, neighborhood pharmacists owned fluoroscopes. He said those fluoroscopes were like “great black boxes” to him and that “those kinds of black boxes don't exist for kids anymore.”
  - dekhn 4y ago
    Many modern bio experiments are almost exactly a repl. You build a system and then repeatedly interrogate it inputing some data using a Read (IE, you pass in some DNA), which is then Eval'd by the cell (warning: there will be side effects), "printed" in the form of some signal like a fluoresence, and then you loop back to the beginning. This is often called "closed loop laboratory." Unfortunately, each step ends up being extremely challenging, and there's tons of noise, and the cost of each Read, Eval and Print is far higher than in a programming language. Further, the "system" is running 38,000 other "threads" all of which have direct read and write access to your data, some of those threads consider your data to be the enemy and cut it up, while others are just randomly spamming your console with uneccessary debug log messages. We have actually reached the point where some scientists have synthetically created a novel chromosome, and used a preexisting cell to bootstrap the new genome so that the cell eventually contains only protein from the new genome. To me, that represents a step beyond tinkering: it means we can create synthetic lifeforms with exactly and only the details we want, which makes studying them and engineering them far easier. Interestingly, even though this tech exists, nobody has found any interesting use for it and it's not even really used to probe biology. A better example would be gene therapy, which has been developing slowly over decades. A single person died in the a trial in the 90s and stopped development (that's the regulation part you're referring to) for decades. In other trials that don't include gene therapy, patients routinely die and they're just a statistic.
glofish 4y ago
Those looking for a proper and comprehensive introduction into genomics from a programmer's perspective should try the Biostar Handbook: https://www.biostarhandbook.com/ https://www.biostarhandbook.com/ I have learned so much from it. It is an introduction into what is like to do genomics in a scientific environment. The content at the link the OP posted appears to be an oversimplified, high level and naive overview
- Ultimatt 4y ago
  The opening paragraph of this resource states its absolutely not about being a comprehensive introduction to genomics. I strongly disagree with the sentiment its naive or oversimplified. It's trying to give someone with no knowledge a working mental model to begin to dig into building a comprehensive view. A framework of analogy for many people is an extremely helpful device for learning, frequently left out by comprehensive scientific or engineering texts.
- nosianu 4y ago
  Actually, I would throw this into the ring instead: https://www.edx.org/course/introduction-to-biology-the-secret-of-life-3 https://www.edx.org/course/introduction-to-biology-the-secre... by Professor Eric Lander > Introduction to Biology - The Secret of Life > Explore the secret of life through the basics of biochemistry, genetics, molecular biology, recombinant DNA, genomics and rational medicine. It's really well done and genomics is the focus. I took many dozens of edX and Coursra courses over the years, this is one of the top 5% of the courses there I would say. I don't understand the phrase "from a programmer's perspective", or "for Engineers" in the title on top. As a programmer whos studied CS but also took numerous life science courses throughout my life. You want to learn biology you study biology, what does a "programmer's view", or an engineer's, have to do with it? You use the correct tool for the job, and having a background in both, I don't see this working out well, more like the opposite actually. The point of looking at biology for an engineer or programmer should be to broaden ones horizons, not to use ones internal models build for a completely different field in another one that really is not like that at all. IMO it's best to forget all computer metaphors here. ---- By the way, since there was something about this yesterday, there also is this course: https://www.edx.org/course/principles-of-biochemistry https://www.edx.org/course/principles-of-biochemistry - it too is very good. A good knowledge of organic chemistry is a prerequisite, but there are plenty of equally interesting course resources for that available too, including even Khan Academy (https://www.khanacademy.org/science/organic-chemistry https://www.khanacademy.org/science/organic-chemistry), or to give a(nother) random link, https://ocw.mit.edu/courses/5-12-organic-chemistry-i-spring-2003/ https://ocw.mit.edu/courses/5-12-organic-chemistry-i-spring-... Biology becomes a lot more fun with this foundation already established in ones head.
ramraj07 4y ago
Starts with “ This Guide is written specifically by and for computer scientists and engineers” And yeah it shows - contrived example after another, and honestly not a great description of anything. If you want to truly understand genomics you have to understand how biology works. And honestly it’s great info for anyone even if you’re not getting into genomics or whatever.. why would you not want a working model of how life is put together? In that case I’d just recommend dusting off a biochem or cell bio text book and reading just the first 5-8 chapters. Typically they lay it out very simply from basic principles and the authors have far more experience and understanding and writing help than this weird tutorial course thing.
- ArchD 4y ago
  Do you have an example of a contrived example and explanation of why it is contrived, for the non-biologist to see why it is contrived? I once tried reading a few chapters of a bioinformatics book explaining DNA, RNA, protein creation, etc. The basic idea seems very simple but to my mind they explained it non-systematically with too many words. There seems to be an internal information structure in these RNA- and DNA- related processes that was not being concisely presented and it seemed that if the writers presented the material in terms of computer-science concepts, so much time could be saved.
  - noipv4 4y ago
    e.g. https://learngenomics.dev/docs/next-generation-sequencing/next-generation-sequencing https://learngenomics.dev/docs/next-generation-sequencing/ne... There's nothing about sequencing by synthesis, how blocking nucleotides are added one after another, pictures of the fluorescent nucleotides on the flow cells are image analysed, etc. This site looks like an ELI5 kind of treatment.
  - gravelc 4y ago
    You can't present it as computer science concepts because it's not computer science. For example, the central dogma of DNA transcribed to RNA translated to protein seems simple, but it's not. In almost every instance, there are vague 'rules' and many many exceptions to these rules. For example, often coding regions in genes start with an ATG, but sometimes they don't. Sometimes splice sites (where the non-coding parts of transcripts called introns are chopped out) can be predicted, but a portion of the transcripts are not spliced at predicted sites for no obvious reason. Sometimes the predictions are just wrong. Sometimes the generated proteins are modified at specific locations which impacts their function, but again, sometimes not. Even whether the gene itself is 'switched on' (i.e. able to be transcribed) is impacted by many many things, such as unidentified transcription factors, or whether the chromosomal location itself is accessible or not. There are many many other things that impact the process. There is no simple underlying concept as the system is not designed, it evolved and is quite different among different organisms, and even in different tissues or timepoints in the same organism. As long as it works and provides enough benefit to avoid negative selection, that's enough. It's a mess, which makes it interesting.
gravelc 4y ago
Don't want to be too disparaging, but this to me doesn't seem to be an 'Introduction to Genomics', but more an introduction to read mapping and variant detection in human (or more broadly diploid) genomes. Genomics stretches vastly beyond this - assembly and annotation to start with. I'd argue the most interesting problem space for software engineers is outside of what is covered in the document.
- Ultimatt 4y ago
  The space of startups cashing in on genomics but making shiny web apps that software engineers need to understand something about human diploid genetic variation is far higher though. Thats where the money and engineers are, not in fundamental algo development for slimemould assembly.
faizshah 4y ago
One of my favorite books in this space is “BioInformatics Data Skills.” It’s just nice concise coverage of a lot of basic tech skills like git, bash, tmux etc. and then coverage of basic bioinformatics skills. For me coming from a SWE background the computational skills are very easy to pick up especially if you work with bioinformaticians you can ask questions. It’s the genomics knowledge that is very difficult for an engineer to acquire.

310 points by froggychairs 4y ago

I find the field extremely interesting, but I wish the pay in genomics was better. Compared to fang/unicorn type companies, their pay is way below market and it's really hard to justify the massive pay cut.

f6v 4y ago
> their pay is way below market The pay is exactly where market is. There’re ton of wet-lab people wanting to get into “data”. And the industry is less lucrative than showing ads like Google does.
- nextos 4y ago
  I think Calico (Alphabet) pay is not too far from a SWE at Google. However, this requires a PhD and much more experience.
  - f6v 4y ago
    Just about any “bioinformatics” job requires a PhD in biology-related field. And there’re plenty graduates. That’s the thing, there’s plenty of supply.
    - the_only_law 4y ago
      Yeah but… > This Guide is written specifically by and for computer scientists and engineers. How many engineers already have a bio phd. Who on earth is this actually written for.

qualudeheart 4y ago

Does this touch on recent developments in information biology?

rainmaker124 4y ago

CS person with biology PhD here. The mix of biology and computation is huge, and with the right skill set, interdisciplinary unicorns make tons of money. If you want to see how computation and biology mix, first dive into a standard university Intro Biology course, and then with that foundation, look into computational biology & bioinformatics (they're distinct). You'll find that genomics is only one piece of a much bigger and absolutely fascinating story. To get that basic biology foundation, another post mentioned an EdX Intro Biology course, that would be a terrific start, or just get a recent university-level intro biology textbook. It's not terribly difficult material and you'll be in far better shape than reading a biology-for-laypersons pamphlet.

Exendroinient00 4y ago

Surely sellouts working on ads won't interject the comment section.

zach_garwood 4y ago
Wow, those are some sour grapes you got there!
- Exendroinient00 4y ago
  Almost every thread covering non web/finance fields of software have loads of comments about pay as the first priority derailing entire discussion.

guy4242 4y ago

It's difficult to get into this field if you don't have a graduate degree. I was a double major, Computer Science and Biochemistry, with a minor in Biotechnology. I sent my resume to many biotech and pharma companies, but could not even get an interview. A lot of the jobs said you need 0 years experience if you have a PhD, but 10 years experience if you have a Bachelors. Now that I have 10 years experience as a developer, I've forgotten almost everything I learned in my science education, and I've lost interest.

civilized 4y ago

Really glad to see this, but it reminds me of the earlier HN post that said engineers don't go into genomics because it doesn't pay and requires a lot of investment in learning biology.

firstplacelast 4y ago
https://news.ycombinator.com/item?id=33671264 https://news.ycombinator.com/item?id=33671264 ^Most recent discussion I’ve seen. I worked in genomics, left this year because you’re underpaid and often disregarded “IT-help” that assists wildly over-educated and underpaid people driving the actual research in 95% of cases.
- tetris11 4y ago
  Thats why you stay though, the people are interesting and the work is meaningful and you directly see the fruits of your labors whilst contributing to a codebase that is by default open source.
  - fncivivue7 4y ago
  - deleted 4y ago
    [deleted]
  - firstplacelast 4y ago
    People aren’t anymore interesting than anywhere else. Work is no more meaningful than anywhere else. It’s a big “selling point” for the industry, but it’s just a way to get people to get paid less (yay you’re making the world better than all those garbage people serving coffee or healing sick people or keeping your lights on or optimizing the routes of the goods you have delivered). If you want sustainable systems, trying to be a martyr and work for less only screws this up long term. Code-base is not open-source. It’s biotech R&D, there is zero culture of sharing outside your organization within industry. You can present high-level things at conferences and such, but you’ll have to rip the raw data out of their dead hands…not happening. I’ve been in too many conversations about building software to serve larger groups in this industry. It can happen, but it can’t currently and nobody wants it. Confident someone will find a solution, but everyone wants their own home-grown solutions in their own walled-gardens that no one has access to. Data and the things it can/can’t tell you are held tightly in these companies. I was at a pharma a couple years ago where researchers were explicitly told they COULD NOT test certain compounds in a certain way because they did not want a trace of this data to exist while they were trying to push compounds through the FDA.

penciltwirler 4y ago

Nicee, but I feel like really the only thing you need to know as an eng is DNA -> RNA -> Protein. Sometimes RNA -> DNA via reverse transcriptase. Everything else is just normal Python scripting.

joshuahedlund 4y ago
That’s what I thought too until I learned about - the dna that doesn’t code for proteins but makes up the vast majority of human dna - the intron regions of genes that are translated into RNA but then sliced out of the RNA and not transcribed into protein and are 5x larger than the coding parts Those two things alone are absolutely critical to understand to interpret a genome sequence. Of course there is much more.
greazy 4y ago
...no. There is more to genomics than python scripting. This is widely incorrect assumption. A new generation of bioinformaticians and computational biologists are using rust, go, and the web to create, share and deliver. Checkout nextclade.org
aquafox 4y ago
You do know that there are things like epigenetics, DNA repair (using specialized proteins), RNAi, post-translational modifications, metabolites (just to name a few)?
otherme123 4y ago
Sooner or later you'll have to learn all the other stuff in the linked page: file formats used only in genomics, structural variants, NGS, evolution, regulation, polygenics, etc.
epgui 4y ago
I’m a biochemist + software engineer, and while I understand where you’re coming from, IMO that’s a very harmful/self-sabotaging attitude. As soon as you start touching science, everything is important.
janeway 4y ago

yuppiepuppie 4y ago

Genomics is where I started learning how to program. Having worked as bench scientist in a genetics lab I understood nothing about my lab mates research when they were showing me python scripts of their analysis. Which initially got me curious. Now having been in the in the industry developing apis for large companies for the past 8 years, I’d be keen to get back into it. Any ideas where to start or find jobs in the space? I would love to go back into the space.

chairhairair 4y ago
I have a similar story with chemistry. I’d also like to get back into the sciences, but I’m not sure how relevant programmers are.
- feet 4y ago
  Very relevant and becoming moreso. Check out job postings at research institutes and universities with healthy research departments
  - zelphirkalt 4y ago
    How does one know, whether they are healthy or not?
    - feet 4y ago
      Generally if they are producing consistent, high quality research

dddiaz1 4y ago

I have absolutely loved working in genomics. I am a huge believer that genomics will be a huge part of healthcare in the future, and i have two examples to motivate that point that I think may be interesting to the reader. 1) The Moderna vaccine was made with the help of illumina genome sequencing. They were able to sequence the virus and send that sequence of nucleotides over to moderna for them to develop the vaccine - turning a classically biology problem, into a software problem, reducing the need for them to bring the virus in house. 2) Illumina has a cancer screening test called Galleri, that can identify a bunch of cancers from a blood test. It identifies mutated dna released by cancer cells. This is huge, if we can identify cancer before someone even starts to show symptoms, the chances of having a useful treatment dramatically go up. Disclaimer: I work for illumina, views my own. I wrote some more about why genomics is cool from a technical point of view here (truly big data, hardware accelerated bioinformatics) : https://dddiaz.com/post/genomics-is-cool/ https://dddiaz.com/post/genomics-is-cool/

pinkwinds 4y ago
Purposefully blocked for certain countries? "The Amazon CloudFront distribution is configured to block access from your country."
agumonkey 4y ago
what kind of math/cs/algorithmic skills do you think one should work on to get a job in this kind of company ?
- jghn 4y ago
  There are two main flavors of jobs. For one you’ll want to be a phd in something like physics or math. For the other Amy standard software engineering background will do.
mtlmtlmtlmtl 4y ago
The thing I'm most excited about long term is biocomputing. Having Turing complete programmatic control over biological systems has an absolutely endless list of transformative applications. Imagine being able to program bacteria that can "infect" the patient and attack tumor cells, or act as fodder to keep autoimmune disease in check. Or let's say we could program stem cells into "liver repair mode" to go and differentiate into new liver cells. Then the implications for things like drug synthesis with the ability to programmatically control enzyme levels to compile more or less arbitrary biosynthetic pathways into fast growing photosynthetic algea, turning CO2, water and sunlight into medicine. It's still a long way off being at that level of applicability, but man oh man it's gonna change everything.

ALittleLight 4y ago

I didn't get this from skimming the first page - but what will this let me do? If I take this course will I be able to mess with a cell or will I just learn some stuff about biology. I saw a recent Lex Friedman podcast where the guest talks about "bioelectric patterns" and somehow getting a worm to grow a second head by messing with those patterns. I would absolutely start on this course now if it was a realistic pathway to doing something like that.

pgayed 4y ago
This is the worst outcome of regulation of the life sciences. There is no REPL for the cell. No tinkering allowed. When Marvin Minsky was growing up in New York, neighborhood pharmacists owned fluoroscopes. He said those fluoroscopes were like “great black boxes” to him and that “those kinds of black boxes don't exist for kids anymore.”
- dekhn 4y ago
  Many modern bio experiments are almost exactly a repl. You build a system and then repeatedly interrogate it inputing some data using a Read (IE, you pass in some DNA), which is then Eval'd by the cell (warning: there will be side effects), "printed" in the form of some signal like a fluoresence, and then you loop back to the beginning. This is often called "closed loop laboratory." Unfortunately, each step ends up being extremely challenging, and there's tons of noise, and the cost of each Read, Eval and Print is far higher than in a programming language. Further, the "system" is running 38,000 other "threads" all of which have direct read and write access to your data, some of those threads consider your data to be the enemy and cut it up, while others are just randomly spamming your console with uneccessary debug log messages. We have actually reached the point where some scientists have synthetically created a novel chromosome, and used a preexisting cell to bootstrap the new genome so that the cell eventually contains only protein from the new genome. To me, that represents a step beyond tinkering: it means we can create synthetic lifeforms with exactly and only the details we want, which makes studying them and engineering them far easier. Interestingly, even though this tech exists, nobody has found any interesting use for it and it's not even really used to probe biology. A better example would be gene therapy, which has been developing slowly over decades. A single person died in the a trial in the 90s and stopped development (that's the regulation part you're referring to) for decades. In other trials that don't include gene therapy, patients routinely die and they're just a statistic.

glofish 4y ago

Those looking for a proper and comprehensive introduction into genomics from a programmer's perspective should try the Biostar Handbook: https://www.biostarhandbook.com/ https://www.biostarhandbook.com/ I have learned so much from it. It is an introduction into what is like to do genomics in a scientific environment. The content at the link the OP posted appears to be an oversimplified, high level and naive overview

Ultimatt 4y ago
The opening paragraph of this resource states its absolutely not about being a comprehensive introduction to genomics. I strongly disagree with the sentiment its naive or oversimplified. It's trying to give someone with no knowledge a working mental model to begin to dig into building a comprehensive view. A framework of analogy for many people is an extremely helpful device for learning, frequently left out by comprehensive scientific or engineering texts.
nosianu 4y ago
Actually, I would throw this into the ring instead: https://www.edx.org/course/introduction-to-biology-the-secret-of-life-3 https://www.edx.org/course/introduction-to-biology-the-secre... by Professor Eric Lander > Introduction to Biology - The Secret of Life > Explore the secret of life through the basics of biochemistry, genetics, molecular biology, recombinant DNA, genomics and rational medicine. It's really well done and genomics is the focus. I took many dozens of edX and Coursra courses over the years, this is one of the top 5% of the courses there I would say. I don't understand the phrase "from a programmer's perspective", or "for Engineers" in the title on top. As a programmer whos studied CS but also took numerous life science courses throughout my life. You want to learn biology you study biology, what does a "programmer's view", or an engineer's, have to do with it? You use the correct tool for the job, and having a background in both, I don't see this working out well, more like the opposite actually. The point of looking at biology for an engineer or programmer should be to broaden ones horizons, not to use ones internal models build for a completely different field in another one that really is not like that at all. IMO it's best to forget all computer metaphors here. ---- By the way, since there was something about this yesterday, there also is this course: https://www.edx.org/course/principles-of-biochemistry https://www.edx.org/course/principles-of-biochemistry - it too is very good. A good knowledge of organic chemistry is a prerequisite, but there are plenty of equally interesting course resources for that available too, including even Khan Academy (https://www.khanacademy.org/science/organic-chemistry https://www.khanacademy.org/science/organic-chemistry), or to give a(nother) random link, https://ocw.mit.edu/courses/5-12-organic-chemistry-i-spring-2003/ https://ocw.mit.edu/courses/5-12-organic-chemistry-i-spring-... Biology becomes a lot more fun with this foundation already established in ones head.

ramraj07 4y ago

Starts with “ This Guide is written specifically by and for computer scientists and engineers” And yeah it shows - contrived example after another, and honestly not a great description of anything. If you want to truly understand genomics you have to understand how biology works. And honestly it’s great info for anyone even if you’re not getting into genomics or whatever.. why would you not want a working model of how life is put together? In that case I’d just recommend dusting off a biochem or cell bio text book and reading just the first 5-8 chapters. Typically they lay it out very simply from basic principles and the authors have far more experience and understanding and writing help than this weird tutorial course thing.

ArchD 4y ago
Do you have an example of a contrived example and explanation of why it is contrived, for the non-biologist to see why it is contrived? I once tried reading a few chapters of a bioinformatics book explaining DNA, RNA, protein creation, etc. The basic idea seems very simple but to my mind they explained it non-systematically with too many words. There seems to be an internal information structure in these RNA- and DNA- related processes that was not being concisely presented and it seemed that if the writers presented the material in terms of computer-science concepts, so much time could be saved.
- noipv4 4y ago
  e.g. https://learngenomics.dev/docs/next-generation-sequencing/next-generation-sequencing https://learngenomics.dev/docs/next-generation-sequencing/ne... There's nothing about sequencing by synthesis, how blocking nucleotides are added one after another, pictures of the fluorescent nucleotides on the flow cells are image analysed, etc. This site looks like an ELI5 kind of treatment.
- gravelc 4y ago
  You can't present it as computer science concepts because it's not computer science. For example, the central dogma of DNA transcribed to RNA translated to protein seems simple, but it's not. In almost every instance, there are vague 'rules' and many many exceptions to these rules. For example, often coding regions in genes start with an ATG, but sometimes they don't. Sometimes splice sites (where the non-coding parts of transcripts called introns are chopped out) can be predicted, but a portion of the transcripts are not spliced at predicted sites for no obvious reason. Sometimes the predictions are just wrong. Sometimes the generated proteins are modified at specific locations which impacts their function, but again, sometimes not. Even whether the gene itself is 'switched on' (i.e. able to be transcribed) is impacted by many many things, such as unidentified transcription factors, or whether the chromosomal location itself is accessible or not. There are many many other things that impact the process. There is no simple underlying concept as the system is not designed, it evolved and is quite different among different organisms, and even in different tissues or timepoints in the same organism. As long as it works and provides enough benefit to avoid negative selection, that's enough. It's a mess, which makes it interesting.

gravelc 4y ago

Don't want to be too disparaging, but this to me doesn't seem to be an 'Introduction to Genomics', but more an introduction to read mapping and variant detection in human (or more broadly diploid) genomes. Genomics stretches vastly beyond this - assembly and annotation to start with. I'd argue the most interesting problem space for software engineers is outside of what is covered in the document.

Ultimatt 4y ago
The space of startups cashing in on genomics but making shiny web apps that software engineers need to understand something about human diploid genetic variation is far higher though. Thats where the money and engineers are, not in fundamental algo development for slimemould assembly.

faizshah 4y ago

One of my favorite books in this space is “BioInformatics Data Skills.” It’s just nice concise coverage of a lot of basic tech skills like git, bash, tmux etc. and then coverage of basic bioinformatics skills. For me coming from a SWE background the computational skills are very easy to pick up especially if you work with bioinformaticians you can ask questions. It’s the genomics knowledge that is very difficult for an engineer to acquire.