<p><strong>DISCLAIMER:</strong></p>
<p>I am afraid that you might find a career path in Theoretical Computer Sciences which would lead to ultimately doing research on the origins of life to be too long and too frustrating: this is only a minor application of theoretical computer science techniques, and the frustration of having to learn too many things unrelated to your interests and ultimate goal might deter you before you achieve your goal.</p>
<p><strong>ACTUAL ANSWER:</strong></p>
<p>An exciting field of research in Computer Science, which is very strongly related to (but not limited to) research on the origins of life, is that of <strong><a href="https://en.wikipedia.org/wiki/Protein_design" rel="nofollow noreferrer">Protein Design</a></strong>, and its older counterpart, <strong><a href="https://en.wikipedia.org/wiki/Protein_folding" rel="nofollow noreferrer">Protein Folding</a></strong>:</p>
<ul>
<li>RNA fragments and proteins fold in three dimension according to the attraction of an opposite nucleotide, with each folding achieving a distinct level of energy: the lowest the energy and the most stable the folding.</li>
<li>Understanding how RNA fragments and Proteins fold is believed to be key in understanding their mechanical properties, and the mechanisms that they achieve in cells (cutting, repairing): it is like understanding screws in the mechanical world.</li>
<li>Given a specific nucleotide sequence, the quantity of possible foldings (in two or three dimensions!) is exponential in its length: it is a challenge to design algorithm able to explore the space of such foldings in reasonable time. And when you design such a sequence, you have to explore the space of possible foldings of each of the potential designs!</li>
</ul>
<p>As all hard computational problems, it is studied in theoretical computer science, but also by practitioners in general (one such practitioner asked me once to show that their particular variant of the problem, that they could  solve in polynomial time, was still NP-Hard &quot;because they would like to put on their CV that they could solve a NP-Hard problem in polynomial time&quot;), using heuristics and/or Artificial Intelligence techniques to optimize the resolution of practical instances (as opposed to the theoretical worst case).</p>
<p><strong>PERSONAL NOTE:</strong></p>
<p>While welcoming any newcomer to the joys of doing research in Theoretical Computer Science, given your background in mechatronics, machine learning and deep learning, I would say that you could definitely study and later work in a research team working on protein design (and hence on the origins of life) without having to become a Theoretical Computer Scientist (TCS) to achieve your goal (albeit you might want to learn some of the basics to communicate with TCSs!).</p>
<p>I hope it helps! Take care!</p>

CC BY-SA 4.0
2022-08-03T10:24:48.100Z
Thanks for the answer, greatly appreciated. How closely is protein design related to the problem of origin of life ? I am interested in the laws ( if there are any) that made normal molecules gain complexity and eventually form some kind of proto life. I am actually caught between doing agi research or origin of life research, I had the thought that whatever causes the transition from inanimate to animate might have something to do with proto cognition in nature. Can I transition from protein design to origin of life research?
Kiran
CC BY-SA 4.0
2022-08-03T15:40:02.573Z
I am not a specialist, but my understanding is that "protein design" is much more oriented toward developing commercial solutions than absolute knowledge goals such as understanding the origins of life.

The field of "Complex Systems" would be a better one to study emergent properties in both the origin of life and the origins of cognition (but again, I am far from being a specialist, just a curious (try-to-)know-it-all!)
J.y B.y
CC BY-SA 4.0
2022-08-05T05:19:02.483Z
Thanks for the answer Jeremy. What are your opinions on agi, should I study computational neuroscience or something for a research career in agi or are current agi wannabes like opencog hyperon promising ? I am confused as to what to do for research- origins of life or consciousness/agi.
Kiran
CC BY-SA 4.0
2022-08-05T13:15:22.120Z
What does AGI stands for?
J.y B.y
CC BY-SA 4.0
2022-08-06T08:45:27.580Z
Agi stands for artificial general intelligence, its about true or general human level or super human intelligence, in contrast to narrow ai like deep learning.
Kiran
CC BY-SA 4.0
2022-08-06T14:32:51.140Z
I am not the right person to give career advice: I studied Math as an undergraduate, got a PhD in Computer Science which lead me to be a CS prof for 20 years when I wanted to do psychology stuff with computers (which, luckily enough, I am starting to do). That said, when research is predictable, it is called implementation: rather than choosing what to study in function of your goal, choose to study something you like and then find out what amazing things you can do with it once you got amazing at it.
J.y B.y
CC BY-SA 4.0
2022-08-10T05:54:27.347Z
Thanks a lot Jeremy. Wish you good luck in your agi venture of implementing psychology findings in computers. If I have further queries related to theoretical science , may I reach out to you ? How do I do this email,pm ?
Kiran
CC BY-SA 4.0
2022-08-10T09:46:04.497Z
It is not very much an agi venture, as I am not implementing psychology findings in computers: rather computer findings in psychology :) Feel free to reach by PM, and good luck to you!
J.y B.y
CC BY-SA 4.0
2022-07-21T11:17:26.487Z
2022-12-26T07:17:36.183Z
2022-12-26T07:17:36.183Z
J.y B.y
<p>I am new here. I have a bachelor's in general engineering ( mechatronics) , I have worked as a developer for a couple of years. I have some experience with machine learning and deep learning. I have heard about theoretical computer science playing a role in origin of life research ( like chemical evolution, assembly theory etc, ), where they try to find out what led simple chemicals and structures to form complicated molecules and eventually life. How do I go become a researcher in this field with my background. Should I do a master's in computer science and then a phd in computational biology or something. Or should I do a PhD in theoretical computer science, like algorithmic complexity. Or should I do a PhD in computational biology or just normal biology and learn the required computational tools on the side. I am completely new to this field and would appreciate it if someone could let me know what the latest research is and how do I become a part of that.</p>
<p>Thanks.</p>

<graph-algorithms>
Research and a career in origins of life
Kiran
# Research and a career in origins of life

(Asked by: username_0 on 2022-07-21)

I am new here. I have a bachelor's in general engineering ( mechatronics) , I have worked as a developer for a couple of years. I have some experience with machine learning and deep learning. I have heard about theoretical computer science playing a role in origin of life research ( like chemical evolution, assembly theory etc, ), where they try to find out what led simple chemicals and structures to form complicated molecules and eventually life. How do I go become a researcher in this field with my background. Should I do a master's in computer science and then a phd in computational biology or something. Or should I do a PhD in theoretical computer science, like algorithmic complexity. Or should I do a PhD in computational biology or just normal biology and learn the required computational tools on the side. I am completely new to this field and would appreciate it if someone could let me know what the latest research is and how do I become a part of that.

Thanks.

**Tags:** graph-algorithms


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## 1 answers

### Answer by username_1 on 2022-07-21. Score: 7

**DISCLAIMER:**

I am afraid that you might find a career path in Theoretical Computer Sciences which would lead to ultimately doing research on the origins of life to be too long and too frustrating: this is only a minor application of theoretical computer science techniques, and the frustration of having to learn too many things unrelated to your interests and ultimate goal might deter you before you achieve your goal.

**ACTUAL ANSWER:**

An exciting field of research in Computer Science, which is very strongly related to (but not limited to) research on the origins of life, is that of **[Protein Design](https://en.wikipedia.org/wiki/Protein_design)**, and its older counterpart, **[Protein Folding](https://en.wikipedia.org/wiki/Protein_folding)**:

* RNA fragments and proteins fold in three dimension according to the attraction of an opposite nucleotide, with each folding achieving a distinct level of energy: the lowest the energy and the most stable the folding.
* Understanding how RNA fragments and Proteins fold is believed to be key in understanding their mechanical properties, and the mechanisms that they achieve in cells (cutting, repairing): it is like understanding screws in the mechanical world.
* Given a specific nucleotide sequence, the quantity of possible foldings (in two or three dimensions!) is exponential in its length: it is a challenge to design algorithm able to explore the space of such foldings in reasonable time. And when you design such a sequence, you have to explore the space of possible foldings of each of the potential designs!

As all hard computational problems, it is studied in theoretical computer science, but also by practitioners in general (one such practitioner asked me once to show that their particular variant of the problem, that they could solve in polynomial time, was still NP-Hard "because they would like to put on their CV that they could solve a NP-Hard problem in polynomial time"), using heuristics and/or Artificial Intelligence techniques to optimize the resolution of practical instances (as opposed to the theoretical worst case).

**PERSONAL NOTE:**

While welcoming any newcomer to the joys of doing research in Theoretical Computer Science, given your background in mechatronics, machine learning and deep learning, I would say that you could definitely study and later work in a research team working on protein design (and hence on the origins of life) without having to become a Theoretical Computer Scientist (TCS) to achieve your goal (albeit you might want to learn some of the basics to communicate with TCSs!).

I hope it helps! Take care!

> **Comments:**
> **username_0**: Thanks for the answer, greatly appreciated. How closely is protein design related to the problem of origin of life ? I am interested in the laws ( if there are any) that made normal molecules gain complexity and eventually form some kind of proto life. I am actually caught between doing agi research or origin of life research, I had the thought that whatever causes the transition from inanimate to animate might have something to do with proto cognition in nature. Can I transition from protein design to origin of life research?  
> **username_1**: I am not a specialist, but my understanding is that "protein design" is much more oriented toward developing commercial solutions than absolute knowledge goals such as understanding the origins of life.  The field of "Complex Systems" would be a better one to study emergent properties in both the origin of life and the origins of cognition (but again, I am far from being a specialist, just a curious (try-to-)know-it-all!)  
> **username_0**: Thanks for the answer Jeremy. What are your opinions on agi, should I study computational neuroscience or something for a research career in agi or are current agi wannabes like opencog hyperon promising ? I am confused as to what to do for research- origins of life or consciousness/agi.  
> **username_1**: What does AGI stands for?  
> **username_0**: Agi stands for artificial general intelligence, its about true or general human level or super human intelligence, in contrast to narrow ai like deep learning.  
> **username_1**: I am not the right person to give career advice: I studied Math as an undergraduate, got a PhD in Computer Science which lead me to be a CS prof for 20 years when I wanted to do psychology stuff with computers (which, luckily enough, I am starting to do). That said, when research is predictable, it is called implementation: rather than choosing what to study in function of your goal, choose to study something you like and then find out what amazing things you can do with it once you got amazing at it.  
> **username_0**: Thanks a lot Jeremy. Wish you good luck in your agi venture of implementing psychology findings in computers. If I have further queries related to theoretical science , may I reach out to you ? How do I do this email,pm ?  
> **username_1**: It is not very much an agi venture, as I am not implementing psychology findings in computers: rather computer findings in psychology :) Feel free to reach by PM, and good luck to you!  

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