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Systems Biology and Biotechnology

Coursera · Icahn School of Medicine at Mount Sinai · 2 HN comments

HN Academy has aggregated all Hacker News stories and comments that mention Coursera's "Systems Biology and Biotechnology" from Icahn School of Medicine at Mount Sinai.
Course Description

BiologyMolecular BiologyDynamical SystemsMatlab

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  • Ranked #26 this year (2022) · view
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This course is offered by Icahn School of Medicine at Mount Sinai on the Coursera platform.
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Hacker News Stories and Comments

All the comments and stories posted to Hacker News that reference this url.
> how long ago did you take those courses?

It took me one year to go through the specialization on system biology at Coursera. In overall I estimate it took 3 years of online courses. The Edx course (intro to...) is very interesting and demanding but it is mostly about core concepts and historical aspects. As ArtWomb said you will not learn state of art information in this course.

> Would you suggest me to take any of them?

Why not, but it depends on what you already know, the time you have, etc...I was used to R&D methods and culture beforehand because of my job.

> How do you go about doing such specialization? It's on Coursera:

https://www.coursera.org/specializations/systems-biology

> Just found a college that had the course and signed up to it? Was that in the US? It was in France, at Rennes I university. There are many low cost opportunities in France, but I felt that the quality of the Coursera courses was much higher than what I learned at the uni.

> Did you end up getting a job at the university to be able to conduct research? Or are you allowed to just visit and use their facilities for that?

I didn't get a job, first because I am old, retired and also because I do not expect to find a so interesting job in a small university in France. A laboratory in a large company would fit my tastes better. The reasons are:

I think what matters is not only the ability to do interesting stuff, you can do as much interesting studies from your armchair than in a university because you can access public and not so public databases and there is an incredible amount of software available for free and people willing to help.

A real glass ceiling is that you must belong to a good team to be recognized for your work:

Scientists do not read single author papers.

The field is filled with in an incredible amount of low quality publications.

For example in my chosen field (ALS research) there is an important work published roughly every two years, yet every week people are claiming to make breakthrough and every year 15,000 papers are published.

Even among recognized scientists there are schools of thought that are incompatible, with contradictory findings never discussed or even addressed. For example nobody agrees on what is causing Alzheimer, Parkinson, ALS, MS, etc...

Important symptoms like muscle wasting are not investigated by muscle scientists who prefer studying neurons.

Even weirder: In brain, glial cells largely outnumbers (10/1) neurons, yet few publications mention them.

It's hard to make a contribution, so I prefer to discuss articles that I find interesting, in the hope to improve a bit the signal/noise ratio.

study_genetics
Thanks for the coursera link, I will jump into that one.

> Scientists do not read single author papers.

Hearing about this fact that a lot of papers get published but that single author papers are kinda discriminated (perhaps that is not the correct term for this) is a bit discouraging but I can understand it. There is no way 15k papers can be reviewed like that, so to a certain point it might make sense. On the other hand, what chance does one then have to make a contribution to the field? PR stunts to get your voice heard? Might be a hard problem to solve.

> Even among recognized scientists there are schools of thought that are incompatible, with contradictory findings never discussed or even addressed. For example nobody agrees on what is causing Alzheimer, Parkinson, ALS, MS, etc...

This is one of the things I want to be able to better understand as I study in this field. Why is that? My current view of things is that some characteristics of the disease being studied should be common on all cases, so there should be at least some consensus on "what is the thing that is wrong that is common among all those cases?" that could then be studied to figure out how that thing being wrong causes the disease. But it could be just that I am still too ignorant on the subject and don't know what is the depth of this discussion.

> I think what matters is not only the ability to do interesting stuff, you can do as much interesting studies from your armchair than in a university because you can access public and not so public databases and there is an incredible amount of software available for free and people willing to help.

This is something I find to be awesome. I have been poking around some resources such as encodeproject.org and ncbi and the amount of information available is incredible. The issue I am having with them is that sometimes information doesn't match (for example, the address of a gene is different depending on what transcription description I am looking at). Because of this, I get a feeling that relying on the information that is made available online alone might not be enough without being able to verify that the data you are working on actually is correct. Is this something that is feasible? Or would this field be mostly trusting data from others and then working with it and hoping it is correct?

BTW, I tried visiting your blog, but it seems that the navigation of posts is broken. Whenever I try to click the links to see posts from previous years I get a 404 page. If you ever get that fixed, would you mind dropping me a line? I wanted to read your first posts to see how your studies in the field evolved.

JPLeRouzic
> "what is the thing that is wrong that is common among all those cases?"

That's the easiest part, usually it is achieved since a long time. But biology is incredibly complicated, much more than everything else. It's certainly not something linear with one causal event and a unique consequence. Beings have selected multiple pathways to achieve a function during million of years. Multiple systems are interacting and changing roles. For example there is not a unique immune system but a galaxy of components assuming different roles at different times.

And technology plays an important role, a century ago we were unable to discern anything else than neurons in a brain, now we can "see" multiple glial cells. How to theorize about something we do not know as existing?

> On the other hand, what chance does one then have to make a contribution to the field?

The best is to work with scientists to solve some issue and them publish with them. I once talked with someone who did that with success. So the problem now is to meet scientists. The easiest way is to present a poster in a conference in order to meet a maximum of scientists at a low cost. If you are not accustomed to "posters" it's a one page summary of what is often a future paper. Master and PhD students are accustomed to present posters but usually there is no other entry barriers than the cost of attending the conference (~$800).

> for example, the address of a gene is different depending on what transcription description I am looking at

Probably because they use different reference genomes. The reference genomes are arbitrary, all humans have slightly different genomes. See: https://en.wikipedia.org/wiki/1000_Genomes_Project

> I get a 404 page

Many thanks, I will look at this ASAP.

Jun 18, 2021 · yolosholo on Biochemical Pathway Maps
What resources are you using to self-learn synthetic biology? I'm also interested in the topic.

I'm looking for something more practical and hands on at this point. I was planning to start my home late in the next month or so, and start with some basics bacteria projects. So far I found the following to be useful:

1. EDX principals of synthetic biology: https://www.edx.org/course/principles-of-synthetic-biology

2. Coursera systems biology: https://www.coursera.org/specializations/systems-biology

3. Coursera Industrial biotechnology https://www.coursera.org/learn/industrial-biotech

4. SBOL https://sbolstandard.org

5. This GitHub: https://github.com/websemantics/awesome-synthetic-biology

6. https://barricklab.org/twiki/bin/view/Lab

7. Synthetic biology primer (book)

joshuamcginnis
I use two microbiology and mycology books I bought on OfferUp for $10, YouTube and papers. The vast amount of my learning comes from breaking larger technical goals into a series of smaller hands-on projects and then troubleshooting my way through. It's hard to give general advice on synbio since it's such a broad field and my journey principally involves a focus on fungi. In my case, I learned to grow all kinds of mushrooms and fungus at home. That lead me to learning DNA barcoding of fungi which has now lead me to DNA transformation of fungi. Feel free to send me more info about the direction you want to head in and I'd be happy to give you some feedback.
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