[laughingman2]

I am working on RL and robotics. I came across Levin in Lex's podcast. And then went on a binge of his other podcast appearences. I agree totally with you, I would very much like to build agents that adapt to different circumstances like "simple organisms". I am not familiar with biology, but I plan to build competence here to follow Levin's work to a point that I could potentially collabrate with biologists or learn from their work. Any suggestions (books etc) that would be salient towards this goal is much appreciated!

[ly3xqhl8g9]

I also focused on the work done by the Levin lab after the Sean Carroll podcast [1]. In order to familiarize myself with the subject matter in a more practical manner I started writing a wrapper and a frontend, BESO [2], BioElectric Simulation Orchestrator, for BETSE [3], the Bio Electric Tissue Simulation Engine developed by Alexis Pietak which is used by the Levin lab to simulate various tissues and their responses based on world/biomolecules/genes/etc. parametrization. Reading the BETSE source code, the presentation [4], and some of the articles referred through the source code has been a rewarding endeavour. Some other books I consulted, somewhat beginner friendly were:

    2018, Amit Kessel, Introduction to Proteins. Structure, Function, and Motion, CRC Press
    2019, Noor Ahmad Shaik, Essentials of Bioinformatics, Volume I. Understanding Bioinformatics. Genes to Proteins, Springer
    2019, Noor Ahmad Shaik, Essentials of Bioinformatics, Volume II. In Silico Life Sciences. Medicine, Springer — less basics, more protocol-oriented
    2021, Karthik Raman, An Introduction to Computational Systems Biology. Systems-Level Modelling of Cellular Networks, Chapman and Hall
    2022, Tiago Antao, Bioinformatics with Python Cookbook. Use modern Python libraries and applications to solve real-world computational biology problems, Packt
    2023, Metzger R.M., The Physical Chemist's Toolbox, Wiley — a beautiful story of mathematics, physics, chemistry, biology; gradually rising in complexity as the universe itself, from the whatever (data) structure the universe was before the Big Bang to us, today.

    somewhat more technical:
    2014, Wendell Lim, Cell Signaling. Principles and Mechanisms, Routledge
    2021, Mo R. Ebrahimkhani, Programmed Morphogenesis. Methods and Protocols, Humana
    2022, Ki-Taek Lim, Nanorobotics and Nanodiagnostics in Integrative Biology and Biomedicine, Springer

In video format I particularly watched Kevin Ahern's Biochemistry courses BB 350/2017 [5], BB 451/2018 [6], Problem Solving Videos [7].

[1] https://www.youtube.com/watch?v=gm7VDk8kxOw

[2] not functional yet, https://github.com/daysful/beso

[3] https://github.com/betsee/betse

[4] BETSE 1.0, https://www.dropbox.com/s/3rsbrjq2ljal8dl/BETSE_Documentatio...

[5] https://youtu.be/JSntf0iKMfM?list=PLlnFrNM93wqz37TUabcXFSNX2...

[6] https://youtu.be/SAIFs_Mx8D8?list=PLlnFrNM93wqyay92Mi49rXZKs...

[7] https://youtu.be/e9khXFSU6r4?list=PLlnFrNM93wqzeZvsE_GKes91C...

[zaroth]

Late to post this (found from a cross-link on another post) but just have to say, this right here is HN comment gold.

What an incredibly helpful and useful response!!