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Yogi Jaeger
@yoginho
, 8 tweets, 4 min read Read on Twitter
An interesting commentary! As far as I understand, it makes two main points: (1) we should focus more explicitly on non-linearity in biological regulatory processes, and (2) gene networks act under the constraint of their (biophysical) context, which contributes to cell function.
Nick Monk & I have made point (1) – focus on non-linear processes – already a few years ago: embor.embopress.org/content/16/9/1…. There are some interesting references in our article that those interested in the topic may find useful.
Also: focusing on the orchestrated non-linear dynamics of biological mechanisms is at the centre of Bill Bechtel’s work. E.g.

sciencedirect.com/science/articl…
sciencedirect.com/science/articl…

journals.uchicago.edu/doi/abs/10.108…

Pity this work does not get the citations it deserves...
As for point (2), there is some really good work on constraints and their role in organismic organisation. A good entry point is here: sciencedirect.com/science/articl…. Book-length treatment here: springer.com/de/book/978940….
What really astonishes me is that the authors discuss causality & constraints without any reference to the classic work of Maturana & Varela, Rosen, Kauffman, Ganti, and many others. A modern incarnation of this type of work can be found here: sciencedirect.com/science/articl….
Don’t get me wrong: this article makes a number of important & valid points. I agree on most of them. It’s just that these points have been made before, more detailed & clearly. A missed opportunity to provide a guide to this previous literature… Pity.

And one last complaint: what do “machine learning” and “control policies” have to do with causality?? Absolutely nothing, as far as I can see. Do correct me if I’m wrong…
I’m sorry I forgot to mention the extremely interesting work of Ingo Brigandt, on modelling and dynamic mechanistic explanation in evo-devo & systems biology:

sciencedirect.com/science/articl…

link.springer.com/chapter/10.100…

Definitely relevant in this context!
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Yogi Jaeger
@yoginho
@CormacORafferty @vicluqmar @WiringTheBrain Whether philosophical contributions to a specific science should be interesting to its practitioners is an interesting question. Much of biology has become so technology-driven & theory-averse that conceptual insights are not recognised even if they address fundamental problems.
@CormacORafferty @vicluqmar @WiringTheBrain Examples: (1) Moreno, Mossio et al.’s work on an organisational theory of the organism. Addresses the fundamental question of what life is. Completely neglected.
@CormacORafferty @vicluqmar @WiringTheBrain Examples: (2) Wimsatt’s criticisms of reductionism in biology. Understanding the limitations of molecular biology & genetics would allow us to escape the intellectual monoculture that biology has become & address some really important research questions at different levels.
Read 6 tweets
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Yogi Jaeger
@yoginho
So, after many live and online discussions with friends on the views of @jordanbpeterson, I decided to actually try and read his “12 Rules for Life.” I got to rule 4 and no known force of nature will get me to read any further in this book… /1
@jordanbpeterson “12 Rules” is an odd mixture between trivial & patronising advice (“Stand up straight with your shoulders back”), wrong-headed pseudo-scientific arguments & persistent hints at the actual unspoken message, which @jordanbpeterson is too chicken-hearted to explicitly express. /2
@jordanbpeterson The advice part makes some sort of sense. Rule 3: “Make friends with people who want the best of you.” Classic stoicism. Not much new here, but for those who need this sort of talking to, the book may actually have some beneficial effects. /3
Read 11 tweets
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Yogi Jaeger
@yoginho
More on networks and their influence on robustness & evolutionary dynamics in today’s “Beyond Networks” lecture (ufind.univie.ac.at/en/course.html…). Slides available here: drive.google.com/open?id=1kfA7R…. @univienna
Evolution requires evolving systems to be robust and evolvable. Non-robust phenotypes cannot be found by evolutionary search, non-evolvable phenotypes cannot produce adaptive variation. This poses an apparent paradox as robustness seems to be the opposite of evolvability. /1
We can start to resolve the robustness/evolvability paradox with Maynard Smith’s wonderful little 1970 Nature paper on “protein spaces.” nature.com/articles/22556…. /2
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