I should have loved biology
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But those kinds of aspirations are completely futile these days. People in the ministries of education and other responsible bodies will argue that high school's purpose is not to educate on a subject in depth but to give a broad overview of many subjects but that's completely besides the point. Because the point is that the only way that they are able to "give you a broad overview" these days is by force-feeding you ever more facts and knowledge in sliced up classes, compressed into ever more shallow and boring text books and then letting you puke it all out in brain dead exams, many times a year for many different subjects, in parallel. Bulimia learning.
Which is beyond sad, because basically every subject can be the source of wonder and amazement if taught the right way and with enough time to explain and explore. Which is why we need to let our kids choose the subjects they are interested early in school and get comfortable with the fact that they won't have any knowledge about other subjects when they leave high school. There simply isn't any other way.
University used to be just the first group, nowadays it includes the second.
With this in mind, I don't see what subject would be safe to sacrifice early in school without danger of crippling some aspect of development. And as for mid-high school, I would imagine specialization is already practiced. High school specialization got introduced in a number of schools in my city in the early 90s - pretty much immediately after the collapse of USSR.
What good does it do?
I don't think that you improve the ability to ingest irrelevant information and make them stick. What you can do is to try to trick your brain into thinking it's relevant - but then, why not make it relevant?
In the end, we don't learn for nothing, we learn because it should help us. If one can't answer why something would be helpful, then I say: don't teach it. If it is helpful (even if it's in the far future) then find a way to show that relevance right now or find something for which the learning is helpful _right now_ on top of the actual purpose.
It sounds like a good goal. But in most cases, it is the opposite - based on memorizing facts or applying simple algorithms. These tasks are easy to measure and standardize, and after reducing their difficulty, ensure everyone can pass.
It's all incentives for the administration (who are the decision-makers), not - students.
Sometimes I ponder what would've happened if I'd have been able to start earlier with using computers seriously instead of opposed to gaming on DOS. I end up with the conclusion it doesn't matter, and that pondering about it means I don't accept the current path I've taken.
Because I had already taken a solid state chemistry class, all I had to do was take a basic introductory biology class; how difficult could that be? It turns out that biology is hard, very hard.
The other students that filled the large lecture hall weren’t ordinary first year students; they were pre-med students. Instead of relaxing by the swimming pool reading a colorful text with pictures of jelly fish and beetles, it felt more like I was taking swim lessons with a few hundred sharks.
The lectures by Professor Luria were great (he had won the Nobel prize four years before) but the number of facts seemed impossible to remember. My fellow students were writing down literally every word written or uttered during each lecture. There wasn’t any mention of jelly fish or bugs or pea plants, but there were complex diagrams depicting even more complex biochemical pathways. I was accustomed to math classes and engineering classes and computer science classes. Biology was very different, more facts and less study of how to apply fundamental principles to prove some theorem or solve some engineering problem.
I survived the Biology class, but it would have been a lot easier for me to take the physics class.
I think that's his point. Your instincts fail you all the time when studying stuff smaller than atoms
Most people don't have a gut feeling for overriding their instincts in favour of math. In fact, when you read some behavioural sciences you'll notice that overriding math with your instincts is the norm
I'm regular puzzled that people think that biology is tractable. It seems to me the best we can hope for towards a complete understanding is a computational generative model.
Indeed the ion channels used by nerves and muscles to send electrical signals are, like, one-way valves for ions
Maths however... It takes me seemingly endless amounts of energy to grasp things. My PhD was in Biophysics, and my colleagues were mostly physicists and they felt the other way around. They didn't understand how it could be harder to derive almost everything from basic principles and techniques than to memorize a colorful story about how life works.
Together we could do nice things though, me drawing pictures on one side of the white board, colleagues writing equations on the other side. It was a nice time.
This is how most things are in my mental model of almost all higher-order concepts and subject areas. Mostly for math, but also for programming/electronics, biology, chemistry, history, etc.
The thing that usually stops me from forming this kind of picture is missing a fundamental concept, or not being able to conceptualize enough of them in my limited exposure to the subject.
The thing to realize is that this isn't a thing that just happens, it's something you can build yourself as you're learning something. Since the visuospatial parts of your brain are the most powerful, it can be an enormously useful thing to do to fit subjects together and reason about them.
Anecdotally, the "easiest" math/engineering classes I had in college were the ones with robust visual representations (control systems with the transfer function block diagrams and mechanism design with a simple graphical way to design linkages where we learned the math afterward).
Real biology involves designing clever wet lab experiments, analysing data to predict new phenomenon, then following up with more experiments.
Nothing in real life biology relies on knowing a huge amount of facts. You just look it up on google.
What makes biology hard to teach is that there are no principles. So teacher can just point to experimental results and ask students to memorise those results. Real biology is about saying the textbooks are all wrong and here is how it really works.
Almost every lecture brought up and highlighted something really cool and fascinating. Like how RNA sequencing over the last couple of years has gone from expensive to almost free, and what its uses are. Or time-lapse of bacteria adapting to antibiotics. Or just the first lecture showing a video of someone sticking a syringe into a cell. There were even some labs that could be done via a normal web browser.
For me this was so much more engaging than the biology I was thought in high school, where we mostly learned things from outdated books.
[1]: https://ocw.mit.edu/courses/7-016-introductory-biology-fall-...
I can recommend 3 really good books, SICP-level good:
1. Biological Sequence Analysis by Durbin et al.
How to model DNA, RNA and proteins as probabilistic languages / generative models. There is also a companion book with all exercises solved.
2. Physical Biology of the Cell by Phillips et al.
A massive amount of quantitative cell biology models that use simple undergrad physics.
Originated from a Caltech course. After reading this book, all other intro to biology books look like a bag of tricks.
3. An Introduction to Systems Biology: Design Principles of Biological Circuits by Alon.
Bacterial circuits from the perspective of an electrical engineer.
Sadly, NSF discontinued funding for a totally epic Cold Spring Harbor Summer school for postdocs that taught [2,3].
A shame, we need more quantitative biology and less bags of tricks.
In undergrad I took a bunch of biology and chemistry classes. It wasn't until I took Biochemistry (a senior level class) that everything came together. The biochemistry class I took was a re-telling of all the stories you learned in molecular biology but with the tools you acquire in organic chemistry.
Equipped with those tools I relearned the Krebs cycle and photosynthesis as real chemical reactions that make sense rather than a chain of facts to be memorized.
The class left me with a deep and profound reverence for life. Every process in a cell has a mechanism that can understood with chemistry. However, the magic of life exists where those processes come together and interact in incredibly complicated ways.
It's seductive to think that we should be able to tease apart this complicated processes and figure out how "life" works, and maybe someday we will. However, it's easy to underestimate the level of complexity and interconnectedness in these systems.
Many of us understand how hard it can be to debug a distributed system. Imagine trying to reverse engineer a distributed system with tens of thousands of interconnected services and messaging queues that all just sort of evolved and were not built with clean engineering practices.
I would go further to describe living systems as not just distributed and so on. Also they are self-assembling and self-repairing. They are redundant - which makes them more damage resistant and 'evolvable'.
Also, these complex assemblies of machines work at (mostly) room temperature and pressure. Except for extremophiles that can work down to freezing or up to boiling temperatures, or in acid or high pressure environments.
Also enzymes catalyse stereospecific reactions, or can use light to drive proton gradients across a lipid membrane, or reduce nitrogen gas. I've always found it funny the sci-fi obsession with 'nanomachines' when living systems are basically composed of exactly that.
Biology's difference from computers is in scope (organisms are whole factories who just happen to have computational abilities by necessity) and origin (organisms aren't designed, and this profoundly and significantly affects everything about them).
This distinction isn't as clear as you think. The active parts of ribosomes (the machines that translate mRNA into proteins) are catalytic RNA. There are organisms that use RNA to store templates (RNA viruses).
There’s 574 amino acids making four separate interlocking chains in a single globin, plus the heme, all just to bind 4 oxygen molecules. It’s simultaneously elegant but hugely complex, far above any discussion of the rna sequencing.
It’s a big part of the “gap” between chemistry and biology IMO.
Not sure if it was from a published paper, but the idea was that early proteins might have been large - say several hundred residues - but mostly disordered.
The smaller, more ordered 'domains' would then have evolved within these larger chains. Recombination and deletion would then have pruned down the disordered parts to leave more efficient smaller proteins.
No idea if that idea makes sense or has any research behind it, but it's quite a neat theory.
Some years back, there seemed an opportunity to create an educational web interactive, a full-scale 3D folding sim, with hands-on direct manipulation, by aiming for plausible-not-correct folding. The simulation literature having built up lots of shortcuts for slashing computation costs, which sacrificed correctness but not plausibility. So one might variously knead a protein, alter it and its environment, and watch it flail. I wonder if anyone ever got around to it?
Humans have the most complicated hemoglobin molecule.
I recall the final exam being only a single question, with a bunch of blank lined pages to write your answer, and the question was something like "You just ate a ham sandwich. What happens to it?" A good answer needed to include everything down to the molecular/chemical level and tie it together all the way up to the macro scale, and I finally felt like that class had prepared me to tell the story.
Maybe toss a line or two in about the complexities of running a large data center and how your response time varies based on some sorcery.
Then you go the extra mile and weave a tale of electrons wrestling with their universe of invisible electromagnetic wave overlords that determine their fate while they embark on a treacherous journey to convey information thousands of kilometers across with blistering speed. Tell them of the aged electron saw a family member get attacked by a stray cosmic ray and the fright of the pack when one simply tunneled out of existence...
Not during an interview, though. The interviewer would see it as trolling (at best), and you would fail the interview. And for a good reason! Because as an engineer (and an intelligent person in general) you must be able to separate what is essential from the non-essential for the subject in question. For instance, the physics or the physiology of the process of pushing a key on a keyboard is probably not what the question was about, nor do those things in fact have much to do with typing, even (which you can do on a touchscreen or using the mouse).
https://aphyr.com/posts/342-typing-the-technical-interview
Oh it was N queens, but the line I remembered was "Summon a linked list from the void."
"You discover a mouse that can sense radiation. How does it do it?"
"You are riding a bicycle. Explain."
We had to do it in 2 pages, NSF grant rules on spacing and margins.
Oh man, where do I even start? Sensory input from the inner ear to balance, the networks that handle feedback from afferent signals from the periphery, efferent pathways to control motor movement. I don't even know all the details but it's mind bogglingly complex. Do I explain the molecular basis of action potentials? The modulating effects of inhibitory feedback within the networks? I feel like all of that barely scratches the surface of the insane complexity of neuronal networks
And how does one even begin to talk about our desire and internal drive to do things like ride a bicycle
It all happens so subtly, and your body does it perfectly with no input from the brain other than "I want to turn".
Assume an experienced rider, as learning is different.
Intention is set, requiring the basal ganglia and fore brain and either a notion of free will, determinism, or whatever you fancy. The area ahead is scanned and mapped for a clear path via retina- optic nerve - visual cortex and particularly the dorsal parietal pathway. Initial organised motor signal sequences originate in pre and pre pre motor areas, hitting motor strip of the brain, particularly those homoncular areas corresponding to legs, arms and torso. Basal ganglia loops prime these circuits into action and help maintain their engagement. Activated motor strip neurons pass through the internal capsule, down the pyramidal tracts, the spinal cord, and meet a lower motor neuron in the anterior horn, which then carries the baton and traverses out if the cord (still the central nervous system) into the body and to the final destination: a muscle. Electrical depolarisation along the axon hops rapidly between nodes of ranvier, enabled by insulation myelination. At the terrminal synaptic bouton lower motor neurons branch across a muscle body. Each neurons innervated patch is a motor unit; multiple combine into a motor pool. Depolarisation triggers fusion of vesicles to the membrane endplate and release of acetylcholine into the thin synapse. Rapid diffusion moves thr snall molecukes to the muscle membrane, the sarcolemma, who then bind to the membrane spanning Nm nicotinic receptors which open and allow a rapid flooding of sodium into the muscle cell syncitium and efflux of potassiun into the extra cellular matrix. Depolarisation of that muscle allows further calcium released from the sarcoplasmic reticulum to activate protein machinery; myosin and actin run across each other and fibres contract. With enough activity concentric movement is achieved across the associated joint. In a manner similar to walking, various spinal reflexes and the spinal locomotor pattern generator create a local, fast framework for actualisation of the impulses. Feed back on state of the musculature ascends the spine via dorsal root ganglia and the dorsal horn. Amongst these are proprioceptive afferents, rapidly feeding back state of tension in muscle fibres from golgi tendon organs along highly myelinated type 1a fibres. These signals pass into the cerebellum where they are co processed with signals from the eyes and vestibular system. The cerebellum modulates the intensity of descending motor activity by comparing expected to perceived muscle state. It also orchestrates balance by integrating general body state, visual cues and vestibular information. In this way the small and large oscillations of riding the bike are maintained and constrained into an orderly process.
Experienced riders can dedicate higher function, i.e Executive frontal areas to other tasks, or to refined modulation of thr task to overcome specific issues. Beginners must use all their frontal powers to focus attention on the task, painstakingly sequence actions, and reflect on the numerous errors and their consequences. Learning is slow, multi system, and largely independent of autobiographical memory.
Think of a even a simple walking protein like Kinesin [1]. What is not shown in the video is that this is all happening in a hurricane of molecules battering it from all sides. Each part of the structure is being pushed, pulled, bent, robot made out of sticks and rubber bands.
That's one of the best things I read all week.
I became interested in biology as a physicist when I realised that all of the problems, on some level, boil down to putting a load of lego pieces in a box, shaking it up with some energy not terribly different to k_B T, and getting a fully-formed, self-replicating lego models out the other end. It's all physics. It's all utterly incomprehensibly mind-bogglingly complex with layers of complexity wrapped around each other, and far out of the realms of either physics or chemistry to compute completely. It's why I work at the intersection of the two fields.
Another famous paper, often-mentioned, related to this is "How a biologist would fix a transistor radio", essentially armed only with a shotgun. The tools of modern molecular biology may be scalpels rather than shotguns, but still, the idea is arguably the same.
Sounds fascinating. May I ask which field that is/what type of work you do?
In their profile
https://www.youtube.com/results?search_query=Drew+Berry+anim...
Meanwhile, later when you get to higher education, math just kind of explode into this creative problem solving field with loads of interesting problems and ways to reason about them, but you almost have to relearn it/properly learn the basics over again when you get there, because you never learned why or how the basics works, just the input and output of the basics.
In high school I really hated biology and chemistry. It was just a bunch of abstract stuff. What made me (re)discover biology was taking up gardening. To me gardening is like applied biology. After a while you really start to get a sense of how it all works and just how unbelievably complex life systems are: photosynthesis, the carbon cycle, the different water cycles, how soil life affects the plants that grow in it, and how incredibly resourceful plants are in interacting with their environment (not to mention insects and other creatures higher up the food chain...)
Bit by tiny bit, and painstakingly slowly.
Evolution promotes fitness enhancing functionality, so we should expect biological processes to be useful for some purpose and hence not be distributed like a random graph (e.g. Erdos Reyni graphs). Indeed, if we look at biological structures, we can find that the causal networks they form are far from random. Furthermore, there are often repeated motifs present. These motifs are quite simple and seem to map neatly onto human understandable concepts (like XOR gates or autoregulators or feedforward networks etc.)
And often, the overall graphs seem like they're tree like rather than some complicated mess of feedback loops (barring autoregulation). This kind of structure is quite modular, and hence we can leverage our understanding of component parts to understand greater and greater pieces of the organism.
There are two problems with this arguement: one, that a lot of the data used for it is not nearly exhaustive. Maybe the people examining biological circuitry stumbled on the rare areas where there are repeated sub-components. Second, even if there are repeated sub components, why should we get modularity i.e. few connections, mostly local?
The former may not be an issue if there hasn't been a lot of dedicated effort towards finding human comprehensible structure in biological circuits, which there might not have been. These things are big and complicated, with many constituent parts, and teasing out the underlying structure may require loads of computation and statistical analysis, which was hard for most of the history of biology.
The latter is not adressed in the book review, or in the comments, but the review author's work makes me it plausible to me that modularity will be common in biological systems. I don't have a good summary of that, or can clearly articulate why I'm hopeful about this. But read the rest of the work of the writer of the article if you're interested in this kind of stuff (key words: natural abstractions, interfaces, selection theorems).
[1] https://www.lesswrong.com/posts/bNXdnRTpSXk9p4zmi/book-revie...
My main problem with it is that it leads to very rigid thought structures devoid of curiosity or contextualization: The belief that the map is the terrain; that the universe is static, predetermined and discretely categorized under conveniently human terms; that scientific knowledge is either divined or standardized by a class of bureaucrats; that things are sorted over a “rank” of lesser to greater according to a direction towards objective progress.
It also generally sucks out a lot of the “fun” of learning about the world (though I understand sometimes taxonomy/categorization _can_ be fun in its own right).
As an example, grammar only really “clicked” with me when I was already in college: I was finally able to see it outside of the “prescriptive memorization hell” that I was subjected to in school, and instead perceive it under descriptive terms of Computer Science.
That's not biology's fault. No language could hope to convey the full ‘personality’ of each character in a tale as rich and complex as unfolds in Lewis' “Life of a Cell”.
But maybe biology is ripe, now that we understand enough of its major 'characters' and their 'behaviors', for us to introduce more abstract models of biology using concepts and language that make for more intuitive players and their relationships. In this way, we might tell a more comprehensible and engaging narrative based on a much smaller set of reusable base models — the way that applied math expands on the concept of a computable function or the way electrical engineering builds on gaussian processes that model signals.
At the very least, I would LOVE for each chapter in a molecular bio textbook to be split into two parts — a short overview of the topic that follows with only the major components and activity described, and only then, to dive into the details. Seeing a city from high above it is an enormous help before trying to appreciate it on foot.
Virtues of the bored
> grammar only really “clicked” with me when I was already in college
For me, it was when I took Spanish in high school. I finally had a reason to know the parts of speech.
Reflecting on this, I find it sad that I never really saw how to place this research into the much broader biological context in which it exists. This goes back to how we teach the subject as the linked article discusses so nicely. There is no sense of wonder. There are no questions that are posed to the reader, just "facts".
Consider this question - look outside at a tree. Where did all the carbon in the tree come from? You may have heard that carbon fixation in plants use a process called "photosynthesis" that involves iron ions. Where did the iron come from? If only we taught by using storytelling techniques and posing questions to students, perhaps we might have more engagement with science than we have today.
(Also as with anything in biology, there is no doubt some weird organism that has like a cadmium or similar in its chlorophyll, I don't know)
I assume that you are referencing the famous 1983 interview with Feynman, in which he playfully says that "trees come out of the air!" For anyone who hasn't heard the interview, it's definitely worth a listen: https://www.npr.org/sections/krulwich/2012/09/25/161753383/t...
I think that level of storytelling is already routine in science education. It just lands differently with different people, especially at different ages. That's why those "things they didn't teach you in school" books are mostly full of things they really did teach you in school, because many people people who are hostile to a subject as teenagers are fascinated by it later. A kid I went to high school with sent an email to a bunch of us about 7-8 years after graduation because he was learning some information about American history that shocked and fascinated him, and he was really worked up about us not being taught it in school. He thought it had intentionally been withheld from us so we would have a rosy picture of our history and our government, but it was all standard bits of American history we were taught in history class. He remembered being bored in class, so he assumed this information wasn't shared with us, but it was, it just wasn't interesting to him at that point in his life.
The sciences are a richly interwoven tapestry of stories, so the question arises, might it be taught like that?
I suggest the bottleneck is that crafting such stories is very very expensive, and very poorly incentivized.
To see this, try taking an existing story, and sampling the neighborhood. In some way broaden or retarget it. Take the "tree carbon source" story. Perhaps make it rough quantitative, say flow vs time of day, as in a "plants consume O2 too - rainforests are only net producers for a couple of hours around noon" story. Or vs lifetime. Or use ocean primary producers, and sketching dissolved gas flows - how recently was consumed CO2 part of the atmosphere? Or sketch a global daily-or-seasonal "inhale/exhale" graphic. Or deep-time context - when did such fixation begin historically, and how has it changed since? Or flow residence times for different biomes? Or a correct telling of "treed sunlight released as campfire redshifted light and heat". Or ...
My experience has been, that if you ask simple, obvious, important-for-integrated-understanding accessible-down-to-K questions, you're pervasively dropped in primary literature searches. If you're lucky, the secondary research literature will catch you. Tertiary literature, like professional "everything about X" too-big-for-a-doorstop tomes are sometimes of helpful, but online are generally unavailable or copyright violations. Sometimes phython/mathematica/R/etc scientific code is regrettably required. Education and outreach content is generally useless - because of scope and focus limitations, when not incoherent and incorrect. And there's much effort, even by the American Chemical Society, to kill off sci-hub. Which will make this all even less plausible.
So I suggest the absence of accessible powerful integrated stories (aka science education that doesn't suck), is a failure of the science research community, not the "science" education community. Because only they have the expertise to create them. Or at least, a failure of research funding to incentivize it. And thus a collective failure to appreciate the magnitude of awesome being left on the table. Assuming sufficient awesome might overcome indifference.
Which is less than clear. "The Sun is yellow" is very popular story. From preK to the most used intro astronomy college textbooks. It's pervasive among even first-tier astronomy graduate students. Also to be found on astronomy education research's lists of most common misconceptions in astronomy education. We've known Sun color for at least a century, had detailed limb tint numbers for decades, and now years of intensive work on stellar atmospheres for occultation, and "science" education content has managed to remain uncoupled from all of it. Getting it right would permit weaving with stories of blackbodies and planetary energy flow and color vision and more. Perhaps someday someone will pay someone enough to care, or finally become sufficiently embarrassed to change. But if anyone expects that will happen this decade rather than next, or the one after, I'd really appreciate to hearing why.
On a more upbeat note, it's been noted that almost all (US) professors in the sciences have been through a small number of institutions. So maybe imagine someone with too much money funding a dozen awesome scientific storytelling programs, and waiting a decade or three?
Or maybe creating good science stories might be promoted as a hobby, for people who were in the sciences but left and so have time on their hands? Sidestepping the massive resource allocation challenge by making it unpaid work.
There's a huge gap between the fundamental units of biology (biochemistry) and the resulting emergent behaviour (living things). We don't have a good bottom-up system to predict the emergent behaviour so we're mostly left with observing from the top down and poking/prodding sub-systems, hoping to gain some insight.
When so much of biology is observation without deep insight, it shouldn't be a surprise that biology is difficult to teach, and even more difficult to find beauty in for new students.
> There's a huge gap between the fundamental units of biology (biochemistry) and the resulting emergent behaviour (living things). We don't have a good bottom-up system to predict the emergent behaviour so we're mostly left with observing from the top down and poking/prodding sub-systems, hoping to gain some insight.
I think this is just about the last thing that we will ever solve/figure out.
There are just a mind-boggling number of parameters, feedback loops, dynamic modifications, interactions, etc that are effecting cellular state (let alone organism state) - something that I think many CS oriented folks ignore when talking about "DNA as source code" (perhaps if program behavior depended on the size of indents, font, variable names, how many lines of code you wrote, the proximity in source location of different functions, etc).
I think I've seen all of those functionalities implemented in esoteric programming languages! Nice comparison.
Oh, and that is being interpreted by more than one incompatible interpreter at the same time.
And then a very similar gap between the fundamental units of one small branch of biology, ecology, where the fundamental units are living things and the emergent behavior is everything you see outside your window! We have a lot of math that explains how things act and evolve together and it's all just the tiniest little smidge of what actually happens.
In the same way, we know a lot of how biology works. Obviously nowhere near all of it; but we are far beyond just scratching the surface. It just turns out that modifying a working complex system is pretty hard.
Wolfram didn't answer "how much would a solar mass of hydrogen cost" for me, but it did tell me that the solar mass is 1.988435×10^33 grams, and another search found hydrogen prices [1] in the range of US$ 250 to 1350 per MT ... So just the financing on building another sun is going to be tricky.
[1] I know it's not all hydrogen but we'll burn those bridges when we get to them.
An analogy would be like understanding how a computer works. We know how chips are made, the physics behind them. We know how bits are stored and processing steps are executed. We also know generally how operating systems work. We have the full compiled code as assembly instructions. But we don’t have the source code of the OS. We just use crude tools to figure out The details of the OS and how it works on particular subsystems but because of the crude nature of the tools the knowledge we gain is ambiguous at times.
My background is neuro, so take that into account. But in neuro, we've nearly no idea about the larger parts of how it all works. Sure, yeah, electrically active neurons, we have that down. But the non electrically active parts? I mean, we're still debating about how much of the brain is glia. Like, we can't even agree on how to count. Don't get me started on synapses.
And just like in software, we can only hope to come with the right levels of abstraction and disregard the irrelevant parts at each level of understanding.
And the analogy with biology actually goes even further - just like in software, we "know" the code (DNA), but how does that translate to the behavior of the complex system (and business requirements in software), is lost to time and the sheer complexity of these systems.
The "anyone" part comes because there are countless parts of those infinately complex systems that have no documentation and no maintainers. They can individually be reverse engineered if it is needed in an individual case, but nobody is going to do that for most of them.
One question I implore you to ask yourself is how much of this “we don’t fully understand it” attitude comes from indoctrination of that way of thinking that you need to have to write grants and aggrandize your own research topic. As Sydney Brenner said a long time back, (in the context of mol bio) the fundamentals have been discovered, we can let the Americans figure out the details.
If we really understood biology, or even just precisely what aspects of a given phenomenon we need to investigate and how in order to understand it, we wouldn't have wasted a decade trying to reduce CVD by increasing HDL. Billions of dollars wouldn't have been wasted chasing the wrong mechanistic hypotheses in Alzheimer's treatment. Cancer would have already been sorted.
Since 15 years ago, extracellular vesicles went from particles used to export rubbish from cells, perhaps with some vague immune involvement, to one of the fundamental mechanisms involved in intercellular communication, carrying nucleic acids between cells.
The reality is the more we understand in biology, the larger we realise biology is and the relative amount of information that still needs to be figured out doesn't change much - especially when you look at it in terms of labour required, because what left is progressively less-low hanging fruit.
Very much applicable to software as well :-) Modern systems are so complex there're very few people (if at all) who understand everything in them, even though they were man-made over time.
It does gunk up but it takes a few decades.
This continuous ion pumping is a major component of the energy consumption of a living being when it is idle, apparently doing nothing.
In the beginning, ionic pumps had only 2 purposes, both essential for the survival of any cell, the first was expelling the ions that can form precipitates and the intake of the useful ions that are not dangerous, and the second was the energy interconversion between ionic gradients and forms of chemical energy like ATP hydrolysis/condensation.
What’s interesting to me, and what follows from this, I think, is that we therefore have a lever for creating more passionate people: create more extremely skilled teachers.
It’s obvious to me that this idea isn’t new; I just wonder why it’s so deprioritized at almost every level of education. (Not least the highest.)
Defund schools and create horrible working and learning conditions for those who stay. Create a problem and then say you are the only one who knows how to fix it. Prey on peoples’s fear, especially fear for their children. Sow mistrust and bigotry in their communities.
Unfortunately far, far too many in power who actively and intentionally do not have the best interests of students at heart.
“There should be no such thing as ‘good schools’ and ‘bad schools.’ All schools should be great.” shouldn’t be be a controversial opinion, but every time I’ve brought it up people get uncomfortable because parents now how precarious their child’s education can be. They’ve seen what has happened in other schools and they don’t want anything bad to happen to their child’s education. So even if things could be better, they fear change and anything that could rock the boat because they don’t won’t it to get worse. And they aren’t wrong to be afraid: how many times has a politician promised to fix education and it turns out the fix is something like one more layer of standardized testing, or cutting art classes, honors classes, special education services to “focus on the fundamentals” while class sizes balloon and the money from those cut classes and services just goes poof?
Further, when a country focuses on CRT and LGBT+-education and Equity-grading at K-12 these days, school is no longer a place to prepare kids for a meaningful career, instead it is a playground to raise future everyone-is-a human rights activist or politician, we will have to rely on skillful immigrants that actually _DO_ things to sustain the economy, this pattern won't last very long obviously.
It's not a teacher's problem, or school's funding problem, it's more of a political problem to me these days(including the recent education-unrelated law changes). I feel lost as an independent.
If anything, schools and educations are harmed by scaremongering and mythmaking like you do.
I think this puts the cart before the horse, and presumes that you can find the right balance of teacher skills to student requirements and that you can maintain that balance year after year.
I honestly think you get more mileage thinking the opposite direction. If you want students with passion and a life long commitment to knowledge, then they're going to need to develop those skills first. At that point, in our modern world, a single oracle of generational knowledge isn't a particularly useful addition.
What you want is generalists that know how to motivate students and to help them find and utilize the resources they need. You might only need a bunch of librarians and proctors and can skip the specialists of the "oral tradition" entirely.
But my humble first year intention was medical intermediate on track to medical school. I absolutely loved biology, and loved the labs most of all. But it was in those labs where I hit a brick wall. With every lab (e.g. dissections etc), we were required to pencil draw our work. A significant part of our grade was on the caliber of fine artistry. I was a scientist damn it! Not an artist. The best I could do was stick figure level illustration. Needless to say I did not shine as a life scientist, so I moved my major into physics.
Looking back I have often wondered how many burgeoning life scientists had their careers cut short in those labs. I have also wondered if I would have stayed stymied artistically my whole life if that had never happened. I love art and would love to be able to draw. Just never went there again.
I didn't pursue anything related to it because it just wasn't my personality. I hated hospitals or touching body parts or even talking to random people. And I hated school with a deep passion (still do long after) can't do much with just 4yr degree in biology might as well lock me up in prison in solitary.
Goes to show, you don't need to be natural at something to do well in it and even if you are a natural doesn't mean it's your thing. There are very few things you can't make yourself learn and be good at by compensating for talent with effort and perseverance.
It did seem like just a bunch of memorization to me then. Much, much later, I took an Extension course in Molecular Biology, and what a difference! I still think the diagrams they draw for biological processes in Molecular Biology of the Cell are just stunningly beautiful, and completely blow away anything you'll ever see in a CS text.
But expecting to have those revelations when you don't know how anything works yet is foolish. You have to pay your dues.
When someone creates a new system, we could argue they have a complete understanding of it, since they build everything from the "ground up". Although even then, they use a particular level of abstraction - not necessarily needing to understand how third-party libraries work, or how it all translates to machine code etc.
Imagine now this person (or a team with equal understanding of the system) leaves, and another team joins. How are they supposed to "understand" it? They would have to piece together everything very much like we're trying to do in biology. Even when the original creators left a "plan" in the form of code, docs or even being accessible for Q&A, they cannot possibly verbalize all the minute details, because the complexity of the system is so large that they would have to spend an equal amount of time on explaining as on developing it. And that doesn't even account for random things or reasons they themselves forgot, or never understood in the first place.
As a result, we're left with only a partial understanding of the system, the level of which goes down the larger the system is. And as more teams join and develop their own pieces and leave, this knowledge gets diluted so much that it becomes hopeless to even reason about the whole thing.
So, I'd argue we can only strive to understand the most important pieces. And, just like we see in biology, the process of their discovery is mostly just educated trial-and-error, aided by the tools like better diagrams to speed up the process. And maybe that's OK, if the ultimate goal is to get to some practical results like curing a disease or expanding the business. We can discover the mechanisms that lead to reaching these goals, but if they aren't relevant, then it's just going to be an academic exercise and another data point in the trial-and-error (until someone discovers how to use it for some new goal!).
That is not the case with biology, if you want to know a part of the stack thoroughly, you in essence have to come up with the "source code" your self.
That's the problem though - code is not enough for understanding. Very well-written and documented code can be, but it's not a given. And the complexity grows exponentially the more of the code there's.
Unfortunately, many managers think the way you describe, while discounting the intangible knowledge that's only in the heads of engineers, and leaves with them. So they treat engineers as disposable units while thinking that possession of the code will guarantee transfer of knowledge.
I’ve always loved biology. The intricacy of the systems, and how they work together is so fascinating and really presses the same buttons as computing.
I have been recently thinking what is actually life - could it be a manifestation of a fundamental physical law? And this article had an interesting take: https://www.pnas.org/doi/10.1073/pnas.1620001114 “How nonequilibrium thermodynamics speaks to the mystery of life”
"Life and its evolution are time-oriented, irreversible phenomena that have produced a steady increase in complexity over billions of years. The second law of thermodynamics is the only fundamental law in physics that distinguishes the past from the future and so this law, and its statistical underpinning, offer the only physical principle that can govern any macroscopic irreversible phenomenon, including life."
Without a grasp of basic physical concepts like conservation of mass and energy and the direction of entropy, life is an impenetrable mystery. For example, imagine a river flowing downstream with eddies on the sides - those eddies have an upstream flow component, driven by the overall downstream energy flow. Living cells do the same thing: they capture physical and chemical energy from their surroundings and use their networks of nucleic acids and proteins, and their encapsulation structures, to reverse the normal downstream flow of entropy.
Everything else follows pretty logically from there. How do cells communicate with their surroundings? They take up materials, excrete wastes, collect sensory data, engage in chemical messaging, and so on. How do cells maintain their nucleic acid and protein networks? By constantly repairing and rebuilding and replicating them using inputs of energy and materials. What is reproduction? A systems-level cellular reboot that also introduces novelty in the form of mutations and rearrangements (which may be useful, or not).
For a good intro to systems-based thinking in biology:
(2020) Systems Biology: A Very Short Introduction, Eberhard O. Voit
https://www.veryshortintroductions.com/view/10.1093/actrade/...
If you want a deep dive into the modern view of the dynamic, 3D genome, this is a great source (which also explains why just knowing the primary sequence of a genome doesn't necessarily lead to an understanding of disease states, failure modes, etc.):
(2015) The Deeper Genome: Why There Is More to the Human Genome Than Meets the Eye, John Parrington
https://www.goodreads.com/book/show/25660581-the-deeper-geno...
Can I summarize it as: Earlier, biology was "hunt and peck" or "observe" ... and now we're moving to a more "rigor of process & ability to create as seen in the past few decades of computer science now applying to biology" type of world?
[1]: https://news.mit.edu/2022/crispr-based-map-ties-every-human-... [2]: https://www.cell.com/cell/fulltext/S0092-8674(22)00597-9 [3]: https://gwps.wi.mit.edu/ [4]: https://string-db.org/
I think some parts are fixable, others are difficult. A part of the problem is that you need to cover some parts in more depth if you want to really make sense of them. Without some basic chemistry and thermodynamics knowledge the entire metabolic pathways seem very arbitrary. This is probably hard to fit into the amount of time you have in school for those subjects.
I presume the author now has that foundation, so it's unsurprisingly much easier to approach.
It would be like if we saved learning how to read and write or learning Arabic numerals and basic number sense until early high school.
One of the most amazing things in nature are the pentameric ligand-gated ion channels. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4412168/
In the same sense, abstracting things is important. Abstraction gives us the opportunity to apply the results from one seemingly foreign field to another.
It is not the task of science to create enthusiasm for the result for people outside the field in technical articles or textbooks as this post tries to endorse.
The excitement for a certain topic should be given by the teachers and, to be honest, this was also always the case in my experience, but I might have been very lucky.
Furthermore, the vast generalisation “Instead, we’re told that if you ever find yourself wanting the area of a triangle, here’s the procedure” couldn't be further from what I've experienced. I’ve never been given a “procedure” in math without being taught why and how it works.
For example, why was the triangle area formula only memorized and not demonstrated to them? I thought this should be standard everywhere in the world? Maybe they just don’t remember, it happens early (age 11-12 for me IIRC).
Similarly, and this is from two decades ago at this point, some basics of gene expression and cell differentiation were covered in my later biology classes, including some of the evolutionary steps. Details are of course fuzzy now. But I clearly remember that learning we share so many genes and so much cell chemistry with even basic bacteria threw me into a bit of an existential crisis when I was 17 — making me question what if anything is so special about humans.
When they were students, some people were simply unwilling to follow any train of thought that was unlikely to be test-relevant. The author almost admits as much: “Someone probably told me that every cell in my body has the same DNA. But no one shook me by the shoulders, saying how crazy that was.” That’s a perfectly fine way to approach school, I’m not judging. But then maybe don’t complain that you didn’t learn anything?
I agree with your point that some students will be more inquisitive, and will need less prompting to do the above thinking themselves. But many (most?) students are not like this, and it’s a shame that many of these students could enjoy a subject that they instead come to loathe.
My passion for biology came when I attended Human Anatomy & Physiology. I learned about neurons and action potentials, chemical gradients and how diffusion can cascade these changes. These machinery like interactions made the cells come to “life.”
I then switched my major to chemistry to understand these interactions. My favorite class was Physical Chemistry. Both of these fields are saturated by two types: the pre-med schooler and the academic, these two types are fighting for prestige and status. I believe the schools mostly cater to these types so they can get into their relevant higher ed (masters, PhD, and medicine) schools. This ends up robbing the undergrads who are actually interested of the material (you end up with what’s described in the article).
In contrast computer science was a breath of fresh air :) I wish bio and Chem fields were like that.
VR anyone?
Some aspects of the field still fascinate me, but I know if I ever bothered to engage the interest I'd be broke.
Brings me to wonder, could we ever create anything so marvellous as what biology does so effortlessly.
I should have loved biology in high school, had it been centered on evolutionary principles, rather than (in my US classes) seemingly disconnected materials with at most a week on evolution.
Because "controversy."
I noticed this essay doesn't used the word evolution at all, preferring "heredity."
Evolution is what ties the fields of biology together, from biochemistry and microbiology to anatomy, animal behavior, and ecosystems.
I didn't start to understand what I was missing in my biology education until I started reading Stephen Jay Gould essays in college.
In college, you have 5 courses per semester, possibly homework and an important test at the end.
The homework has to be finished, essays need to be written and facts need to be learned for tests. All of this times 5. I think the most mentally draining part of it all is the constant context switching.
In the end the hunger of students to delve deeper is not super high, and a lot of lecturers want to stay close to the courses structure they originally planned out (sometimes years or decades ago).
A good lecturer can make one course go a little better, but IMO it's the system that discourages interest.
All anecdata of course. With that said, are there any studies done on this? I have a hunch the answer is not really. If there are some, then my hunch is: not all that much.
If you can’t use language like that you’re giving up on getting anything through to over half of the class. Trying to impart information to people who don’t care and aren’t interested is amazingly hard. Not using agentic framing makes it harder.
I take umbrage with the idea this is a technology from millions of years in the future. It’s literally the background noise technology that just shows up if you do nothing for 16 billion quarters.
*unless you merge with a first cousin.
The problem with teaching science is that the amazing stuff that is accessible to a high-school student was figured out 100 - 400 years ago, and we’ve learned a lot since. And for biology and chemistry, there are all those details. (I guess math might be worse, since we teach things that have been understood for thousands of years, but at least the old stuff is obviously useful.)
I think it’s really hard to teach and test on the exciting stuff. What’s exciting to me may be “who cares” to the next person. But it’s great when it works.
What do I remember from HS bio? Lists and lists of lists, uglenas and pseupodas. Way to kill the buzz.
I finally gave up realizing there was no chance i was getting into medical school with bad GPA and switched to EE where I admittedly had to study a lot less and got much better grades. People underestimate just how difficult bio is and i think the high volume of information and importance of memorization is just training you for medical school where the volume of material you need to study is magnitudes more.
I don't envy anyone who went through it. When it came to physics, math, circuits, etc. you could really get away with just doing a couple practice problems and understanding the core concepts. The experience of going through two very different fields and being an utter failure in one made me believe that people's brains can just be wired differently.
Every attempt I've made into learning a new language has been a failure. I've resigned myself that only through immersion will I ever learn a new language. I suppose there is no equivalent in the medical field. :-)
I find it amazing that we give so much agency to doctors over our health while we know relatively very little about our own bodies and health.
And biology is a big part of that learning.
I now study medical books on my soare time.
Would recommend “Clinical Methods” as your first foray. You will understand your doctor and the biology is immediately applicable in your Daily life. Ie how to deal with fevers in your kids.
After that learn about your skeletal system and biomechanics.
Next Neuro degenerative disease and the brain.
Once you’ve caught the learning bug, you can go into 1st year Med School curricula and then the rest from there.
Some big parts of medicine is relatively useless - psychology for example.
Would recommend learning meditation ina real way and reading “Right Concentration.”. Learning about jhanas and mental states.
I remember as a kid when they asked me what I wanted to do, I never understood why I couldn’t do all of the above.
while I'm pretty despondent with the replication crisis in psychology, medicine isn't much better.
but to dismiss it outright is pretty ignorant. curious how you explain the state of America if your assertion is psychology and mental health are "relatively useless" fields
Eastern techniques seem to be much more practically useful for handling mental health tecniques.
We have done science here, made hypothesis and tested them. "Western medicine", including therapy and anti-depressants, have been shown to have real, significant, reproducible positive impacts.
It's also difficult to compare to "eastern techniques" since that's a fairly vague term. Perhaps drinking tea, meditating, and getting acupuncture has a more positive impact on one person than taking an anti-depressant, but for another person, anti-depressants may be wildly more effective. Perhaps arranging ones house and diet to maximize "positive chi energy" will help one person, but have no impact on another.
What eastern techniques are you specifically claiming are practical and useful, and for what scenarios? Are the studies that show anti-depressants to have effect wrong, or are they useless because they're inferior in your opinion?
Everything you need is in this link: https://twitter.com/nickcammarata/status/1471300341232668679
The capacity for joy at any point of time is infinite - that was revelation for me. Ability to access it - changes everything.
one of these days ¯\_(ツ)_/¯
I admit that I'm biased, but I don't think this could have evolved through random processes. I'm a believer in Intelligent Design.
https://youtu.be/X_tYrnv_o6A https://youtu.be/7Hk9jct2ozY https://youtu.be/fpHaxzroYxg
It's a logical fallacy that complex processes cannot be created from random events. It certainly can, and evidence is abundant.
Biochemistry of life is an advanced form of brownian ratchet [1]. It started simple, but can get to absurd level of complexity due to selective pressure, and memory via genes. And selective pressure is nothing but maximizing for greatest replication.
There are many interesting philosophical questions inside biochemistry, but a Judeo-Christian Diety is not the most interesting.
So goddamn stupid that it's just sad.
> However, this argument is premised on the notion that genes and proteins evolve through a process analogous to tossing a coin multiple times. This is untrue because there is nothing analogous to natural selection when you are tossing coins. Natural selection is a non-random process, and this fundamentally affects the probability of evolving a particular gene.
> ... Modern proponents of intelligent design (ID) are usually too sophisticated to make such an error. Instead, they present a superficially more sophisticated probability-based argument. Their idea is best illustrated by example. ... ID proponents argue that it is the combination of improbability and matching a pattern that makes them suspect that something other than chance or purely natural processes are at work. They use the phrase “complex, specified information” to capture this idea. In this context, “complex” just means “improbable,” and “specified” means “matches a pattern.” ...
> The argument likewise founders on the question of complexity. According to ID proponents, establishing complexity requires carrying out a probability calculation, but we have no means for carrying out such a computation in this context. The evolutionary process is affected by so many variables that there is no hope of quantifying them for the purposes of evaluating such a probability.
Back in the 1990s, the newsgroup talk.origins put together a long index of creationist claims. Your example is http://www.talkorigins.org/indexcc/CB/CB010.html
> The calculation of odds assumes that the protein molecule formed by chance. However, biochemistry is not chance, making the calculated odds meaningless. Biochemistry produces complex products, and the products themselves interact in complex ways.
> The calculation of odds assumes that the protein molecule must take one certain form. However, there are innumerable possible proteins that promote biological activity. Any calculation of odds must take into account all possible molecules (not just proteins) that might function to promote life.
> The calculation of odds assumes the creation of life in its present form. The first life would have been very much simpler.
> The calculation of odds ignores the fact that innumerable trials would have been occurring simultaneously.
It links to further discussion at http://www.talkorigins.org/faqs/abioprob/abioprob.html ("Lies, Damned Lies, Statistics, and Probability of Abiogenesis Calculations")
Richard Dawkin's book "Climbing Mount Improbable" "is about probability and how it applies to the theory of evolution. It is designed to debunk claims by creationists about the probability of naturalistic mechanisms like natural selection." (quoting https://en.wikipedia.org/wiki/Climbing_Mount_Improbable ).
Five copies of the book are available to borrow right now for free (with an account) from archive.org, at https://archive.org/search.php?query=%22Climbing+Mount+Impro... .
All of these explain why your probability calculation is not meaningful.
But the funny thing about that is that the genes for say the 'helicase' looks like it was made by a copy machine, churned out by the millions, for every life on earth. But if you look very carefully, it's not a copy made from a master copy, but copied from each other. There are small mistakes made by this 'copy machine', so that you can trace the different generations of the copy of the 'helicase' based on what mistakes have been accumulated. You dig further, and you can map out different generations and make a tree like diagram. The further away from each other the two helicases are, the more mistakes have been accumulated.
You keep doing that for every life on earth, and you get something like this [1].
And then you dig further and realize that there is no Hand of God there, and creationism is a primitive explanation for something people didn't understand, like how lightning was God being angry.
[1] https://www.sciencedirect.com/science/article/pii/S235234091...
> Here’s the central problem: molecules don’t behave that way. What is portrayed is wonderfully precise movement; it looks like the molecules are all directed, purposeful, and smooth. Take for instance the behavior of kinesin, that stalk-like molecule seen marching in a stately way down a tubule, with two “feet” in alternating step, towing a large vesicle. That’s not how it moves! We have experiments in which kinesin is tagged — it’s towing a fluorescent sphere — and far from a steady march, what it does is take one step forward, two steps forward, one step back, two steps forward, one back, one forward … it jitters. On average it progresses in one direction, but moment by moment it’s a shivery little dance. Similarly, the movie shows the monomers of tubulin zooming in to assemble a microtubule. No! What it should show is a wobbly cloud of monomers bouncing about, and when one bumps into an appropriate place in the polymer, then it locks down. I made this same criticism in my review of Mark Haw’s excellent book, Middle World, which does get it right. For purposes of drama and minimizing complexity and confusion, though, the animators of that video have stripped out one of the most essential properties of systems at that scale: noise, variability, and the stochastic nature of chemical interactions.
> That’s particularly unfortunate, because it is the seeming purposefulness of the activity of the cell that has made that clip so popular with creationists. It fits with their naive notions of directed activity at every level of the cell, and of their denial of the central role of chance in chemistry and biology.
Math, physics, and certain parts of chemistry can actually be done on pen and paper (or by computer simulations) because it is based on solid theory with mathematical underpinnings.
The only solid foundation biology has is descriptive theories from Darwin and maybe Mendel. All other biology must be studied through experimental data, which means wet lab and analysis. Just reading about a result (which is how school is done) doesn’t mean you are a good biologist no matter how well you can regurgitate the textbook.
It isn't really fair to blame bio teachers for not teaching this in the 80's or even early 90's. Prior to that, it was mostly memorization. Some biologists and chemists were putting together the basic facts that came together and gave us an "aha!" moment. They won Nobel Prizes for a lot of that. Without Kary Mullis and PCR in the 80's, we wouldn't know 0.01% of what we know now.
https://www.unz.com/isteve/the-new-2018-pisa-school-test-sco...
Or is it something a little more profound?
Being able to read for meaning, extract information, combine knowledge from two texts, distinguish between what is stated and what’s implied, even to figure out something is implied, all of those are the kinds of things we expect an educated person to be able to do. PISA tests them. Trying to make people care about academic subject matter is very difficult because most people do not care and do not find it useful. Thus they forget most of what they learn in school. Insofar as education is forcing the tastes of one class on everyone else it can burn. Most people don’t care, just like most academics don’t care about sports. Forcing sports on them would also be an injustice.
Ah, yes, we should teach less science to everyone because that would be like forcing every academic to play sports. Perhaps physical and science education should be provided for every student? Education does not come at the expense of sports. If anything, the opposite is often true.
People are naturally curious. Shuffling them into the confines of some narrow and often purposeless maze fucks that up. That's a considerable portion of TFA, the institutional curricula stunted their interest in biology.
My curiosity was drugs, drugs lead me to biology, lead me to chemistry, physics - but it was independent study. Political challenges from my partner got me interested in history and anthropology, but it was all independently structured.
I think if the institution gave all these little knobheads enough autonomy to actually derive, from themselves, some real interest, they would ultimately end up intersecting with all the sciences, it's actually inevitable. Instead they're just forcefed a bunch of information they don't have a relationship with.
Sports is biology and mechanics is molecular biology and kinesiology and so on. It doesn't matter where you start, you track into that shit. Passion the latitude it lends to the people possessed by it is what allows us to push deeper and deeper. Not stunting intellectual growth by conditioning people into a state of repulsion at the premise of learning.
Take, for instance, a FT-working non-trad that scores above the mean. The mean who predominately consists of students who are FT-students. Should some respect not be paid to the considerable handicaps suffered by the non-trad? How do you even begin weight that?
Of course this is multiplied a million times over in several dimensions.
-- John Adams in a letter to his wife Abigail
I'm sure many people would love to have their children study the arts and humanities and develop profound insights into human nature and life itself. Unfortunately, many people are stuck studying mathematics and other subjects like it in the hopes of having a decent career.
I don't normally come to the defence of the biological sciences but why would you expect it to be anything else?
If you're blindly reciting then either you don't understand or haven't been tough enough to understand the parts of the puzzle. Unfortunately this is also a consequence of modern teaching methods I would argue but that's another problem all together...
I would disagree, we see the object code. If we had the source, with comments, genetic engineering would be much easier
Biology doesn't have the same clean levels of abstraction that we've developed in computer science. DNA functionally operates at many levels. It long term storage, local working storage, and it is used to compute. It's a single molecule that does everything.
Then you have to throw in all the secondary processes that modulate and regulate DNA replication, transcription, as well as activation/deactivation.
While it can be useful to lean on the abstractions we've developed to try to understand what DNA is doing those abstractions can only be taken so far.
Human civilization is severely time-limited (or just time-pressed). We can't wait millions of years running a simulation to optimize a little widget. We need to rely very much on high level design and comparatively little on efficiency and optimization. On the other hand, life cannot afford huge DNA (very costly), or energy waste (generally disfavorable from evolution). So human built systems tend to be of a low "Compute complexity": the computational complexity of obtaining solutions and solving problems themselves (like civil engineering structure problems, or design of objects) must be fairly low. For life, systems can be amazingly intricate, every tiniest cell a wonder that would probably take thousands of years for civilization to maybe be able to replicate. But it all ranges from about 130kbp to 8Mbp[1], which would be around 16Mbit/2Mbytes at most. So it fits (uncompressed) in a diskette (floppy).
Even now with powerful computers, we're still mostly constrained by cognition (specially human), you see simplicity all around you.
So if you look at the human world, you see (computational) simplicity everywhere, but the natural world has undergone trillions of generations of optimization to arrive at almost perfect (in an almost literal way) little machines, complicated but with a hidden amazing (size) simplicity.
I think there's a connection to be made to algorithmic inference as well. Originally we came up with ideas for Universal Inference (from ideas from by Solomonoff, Kolmogorov among others) [2][3], the most glaring candidate was the "size prior": evidence explainable by the least algorithmic information ought to be most likely (Solomonoff inference). Later, there were promissing ideas around an additional term: the "speed prior" (from Schmidhuber[4]) -- the biological word is one where the "size prior" (simplicity is most likely) works almost perfectly, and human civilization is one where the "speed prior" (computationally easy is most likely) is helpful.
[1] https://en.wikipedia.org/wiki/Bacterial_genome
[2] https://en.wikipedia.org/wiki/Kolmogorov_complexity
[3] https://en.wikipedia.org/wiki/Algorithmic_probability
[4] https://en.wikipedia.org/wiki/Speed_prior
Side note: I think intellectually one of the ways we're really far behind is recognizing Algorithmic Information theory as a foundation for statistics and metaphysics. We're very stuck making little progress on the metaphysical realm (which physics is advancing more into) because of a lack of widespread acceptance of those advanced tools for science. Algorithmic inference gives a solid basis for comparing metaphysical models and deep questions about the cosmos.
Until I found out C.S. to a majority of the world really just means coding - the most boring activity I can imagine. (to me... I have some parts of "H.D." in the ADHD, so don't downvote me).
I thought C.S. would lead to a career of solving difficult Automata, algorithmic, etc problems. Nope.
It’s certainly not the only way to have that intellectual posture, but it’s a powerful one.
https://boards.greenhouse.io/invitae/jobs/4196489?gh_jid=419...
https://www.recursion.com/careers?gh_jid=3992017 "A biology background is not necessary, but intellectual curiosity is a must!"
https://ekgn.fa.us6.oraclecloud.com/hcmUI/CandidateExperienc...
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Bonus points for pictures!
Is this evolution happening because we have devised means of travelling so quickly? Travellers taking the virus to new populations. The more people infected, the more variants arise? Or is it because vaccinations mean we cull the less-virulent variants of the virus? If we had had no vaccinations, what variants would have evolved, and at what pace?
Why can we eradicate some viruses like polio or smallpox, but, seemingly, not this one? One would have to guess that it's because its means of transmission - through aerosol droplets from sneezes and coughs - is so effective.
Will COVID become as common as the common cold, but forever more deadly?
One thing I don't understand after reading this and several comments, is I'll often hear stuff like "biology is so complex. Everytime you think you understand a piece you find out it's another abstraction on top of another complex system". And then, immediately people say stuff like one comment that I thought was pretty funny: "they are structurally like a cathedral built by a blind deranged architect.".
And also from the article:
> Biology is like this, just much, much worse, because living systems aren’t intentionally designed. It’s all a big slop of global mutable state.
My question is, all these comments describe how biology is an indescribable complexity, and then conclude its so complex because it's just a bunch of random coincidences that built up over time. Just because biology is one big glob of mutable global state, does that mean it wasn't intentionally designed? I know certain algorithms like video encoding/decoding and coding compilers may seem like random pieces of code when you first encounter it. You may also question whether the original authors were just writing "bad code" since it's all so interconnected. But then you learn a thing or two and realize that the process itself is very interconnected, and you can only cleanly separate so much of it, but you'll still be left with a hairy piece of code that's kind of messy but necessary.
Why can't it be the same way with life? We study these astronomically complex systems, and then we talk about how we're still so far away from understanding the system as a whole, then we conclude it's just a soupy mess that all came together randomly. How can we come to a conclusion like that without being able to understand all the intricacies as a whole? How much of biological complexity is necessary complexity, and how much is accidental complexity? And by the way, I am a believer in intelligent design which is why I raise these questions.
I just find it amazing that we can simultaneously speculate about the wonders of life, and then chalk it all up to a bunch of random coincidences haha.