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“The Machinery of Life” by David Goodsell is full of illustrations like the ones show in the article and really gave me a sense of what k might imagine when reading about the cell.
“Cell Biology by the Numbers” by Ron Milo and Rob Philips is full of order of magnitude calculations of about the processes of the cell. How fast are they, over what distance, how much, etc.
There's a searchable database of bionumbers[1], and a draft version of "by the Numbers" officially online[2].
[1] https://bionumbers.hms.harvard.edu/search.aspx [2] https://www.dropbox.com/s/gvpleqtcv8scro4/cellBiologyByTheNu...
Every part of this passage is a shockingly accurate description of myself. I felt that I was bad at math and did a biochem degree because it meant I could skip Cal III. Now, I'm a computational biologist and I've mostly made up with math.
One of the most fascinating parts to me was DNA transcription. The engineering is quite precise.
Found the video I was referring to: https://www.youtube.com/watch?v=7Hk9jct2ozY
For illustration, consider the classic animation of a walking kinesin towing a vesicle. One could jiggle-ify it. But that won't convey that during every step, the vesicle has done a "balloon in a hurricane" exploration of every possible position it can reach while remaining tethered. Won't clarify that the very very misleading "I'm just a peaceful barge" vibe is entirely animation fantasy. Secondary content could have been added to defuse this negative educational impact, but the choice was made to optimize for, and I'm quoting, "pretty".
Jiggle-ification takes perhaps the biggest educational downside of these animations, and makes it even more misleading.
One thing that these animations always remind me of is that speeds at that level are tied to size. We're use to a world where birds and cars are faster than pollen and insects (mostly), but the fidgety twerking of all those big proteins is due to collisions with higher-velocity, invisibly small molecules like water (Brownian motion). When was the last time a pollen grain made you flinch? Everything is kinetic/EM energy exchange; everything is in the gray area between Newtonian and quantum physics. (Shout out to Einstein, but also Boltzmann through Dirac.)
I didn't get the "miles of DNA" reference. A single strand of DNA is approx 3 meter in length when uncoiled. Now I'm thinking how many strands may be replicated at a time.
The painting is wonderful. Yes, it's a snapshot in time of a dynamic state. All paintings are!
Maybe an educational text for the laymen has summarised this recently but I'm not aware of one. Most Biology from your school days have been rewritten.
I will have to re-read Molecular Biology of the Cell, 7th Edition, 2022. I read the 3th edition and it has changed dramatically since.
You can download it on Anna's Archive or order it at the usual suspects https://www.amazon.com/s?k=Molecular+Biology+of+the+Cell%2C+...
The first few Units cover all the basics: chemistry of life and energy, molecular biology, cell biology, and genetics. From there you can branch out into anything.
Curious how perspectives vary. I would have said there's basically nothing available, textbooks being horribly wretched.
I don't know of anything which takes a "bottom up", rough quantitative, engineering first-principles intro to cell bio, let alone to biology. No whys and hows of building close to thermal noise energy levels. No focus on pervasive multi-scale cross-cutting strategies for localization and compartmentalization. No energy budgets, not feel for reasonable numbers, no... sigh. When you see a nifty foundational insight mentioned in passing in a research talk, it's a really good bet it won't be in textbooks any year soon. One of the causal threads leading up to TFA, the Harvard bionumbers database, was born out of someone's 'it's absurdly hard to find numbers'.
Chatting with a cell bio tome publisher years ago, about what absurdly implausible resources would be needed to do something transformatively better, the snark for "but it has 100 authors!" was "nifty - and how many for the second page?". Maybe now with AI we can start nibbling away at this faster.
Very true, these books are qualitative. There's a bit of basic math around delta-G for reactions and Chi-sq tests for genetic associations, but the conventional undergraduate introductory biology course is 99% descriptive.
There are reasonable arguments for taking that approach. These courses are foundations for subsequent study, with the intended outcome that students have a broad but shallow understanding of core basic ideas. Lots of biology makes intuitive, mechanistic, and visual sense, much like introductory computer science and introductory chemistry.
Obviously applied math plays a key role in biology but it tends to address specific needs like protein structure prediction, dynamic modeling of transcription/translation and metabolism, inferring phylogeny, high-throughput 'omics analysis, network simulation of epidemic outbreaks, and so on. These are great to study, but without the broader context the understanding would be relatively fragmented, lacking the big picture.
Rereading OP's question:
> good modern starting points to someone who would want to learn more about how living beings work (from bottom up)?
I interpret that as wanting a general understanding, starting with chemistry and working upwards towards evolution and populations. That's all in the standard two-semester introductory course, hence my book recommendation.
If that's wrong and OP wants a math-centric approach, here are a few gems:
Physical Biology of the Cell, Phillips, et. al
An Introduction to Systems Biology, Alon
Evolutionary Dynamics, Nowack
> The first time I did these calculations, I felt an intense appreciation for biology. And now, I want everyone else to feel the same. We ought to teach students of biology to think as mathematicians: to carefully quantify biology, to think in absolute units, and to develop a feeling for the organism.
It was interesting to read this article, but I think I would’ve understood a lot more if this entire piece had been (or were) an animated video that described it. Text and a few animations don’t do enough justice for the passion, knowledge and detail that’s in this article, IMO.
Bit nitpicky here but ... he wrote a typical E. coli cell.
Naturally bacteria have different size ranges, depending on many factors - nutrients, temperature, genome and so forth; e. g. look at how huge Thiomargarita namibiensis is.
But the 1 µm as average here given for E. coli, is not correct:
https://bionumbers.hms.harvard.edu/bionumber.aspx?id=117344&...
Length 1.78±0.54 μm
So while +/- at the lower end may be 1.24 µm, the max range here would be 2.42 µm, which is what I had more in mind (e. g. roughly about 2µm). I don't have all of the data to be able to say which is the exact value, but I think the website at bionumbers.hms.harvard.ed is more realistic, so I would say that E. coli's best average is more at 2µm than 1µm.
[1] https://commons.wikimedia.org/wiki/File:E._coli_Bacteria_(73...
Hold up, My own inexpert "numerical intuition" is having problems here.
If polymerase converts 40 bases/sec, and travels ~20m /sec, how on earth is one base pair 2 meters long?
I assume what the author means is that the average conversion work done by each protein is 40 base pairs per second, however it spends most the time "seeking" rather than "converting"?