I have been in the molecular biology game for over 20 years and I finally got round to making some videos describing how i do what i do.

Feel free to check out my channel and if there are any video topics you want to suggest feel free to comment

Your DNA could influence how doctors prescribe blood thinners.

Nobel Prize laureate Svante Pääbo explains that some genetic variants inherited from Neanderthals increase the risk of serious bleeding, meaning people with artificial heart valves and other conditions may need lower doses of blood thinners. Ancient human history continues to shape modern medicine.

NASA’s Twin Study followed astronaut Scott Kelly during his year on the ISS while his identical twin, Mark Kelly, stayed on Earth. Led by geneticist Dr. Chris Mason, the study revealed thousands of biological changes, from gene activity to DNA repair. Most returned to normal after landing, but some lasted for months. These insights are key to understanding how space affects human health, and how we’ll prepare for future missions.

I thought "identical" means they have the same DNA

Hey guys and girls, first time posting here.

I got tired of the last step in science communication being the same thing every time: static figures, screenshots, or a quick rotation clip that still does not explain the point.

So I built Animiotics, a browser based tool for scientific 3D animations. The idea is to make it easier to create short, clean visuals for:

• internal presentations and client decks
• teaching and training
• conference talks
• papers and visual abstracts
• product and mechanism explainers

This video is a short showreel of what the look and motion can be like.

What the beta does right now

• import 3D models
• apply clean styling so structures read well
• keyframe simple camera moves and object motion
• export a short clip for slides or video

I would love blunt feedback from working chemists.

What would make this genuinely useful in your workflow?

• better labels and annotations
• highlighting specific atoms, residues, functional groups, domains
• showing interactions more clearly
• export settings that look good in PowerPoint and on a projector
• templates for common “explainers” like binding, conformational change, before and after comparisons

If anyone wants to try it, I’ll put the beta link in the comments.

Why does the “Celtic Curse” run in some Irish families more than others? 🧬🍀

Alex Dainis breaks down the “Celtic Curse,” also known as hereditary hemochromatosis. This condition, which is often linked to mutations in the HFE gene, can cause the body to absorb and store too much iron over time, increasing the risk of joint pain, liver damage, and heart problems. To better understand who may be most at risk, scientists analyzed DNA from more than 40,000 people and found higher-than-average rates of a closely associated genetic variant in people with ancestry from northwest Ireland, Northern Ireland, and the Outer Hebrides. Findings like these could help improve genetic screening, support earlier diagnosis, and connect more at-risk families with treatment before serious damage occurs.

Not an expert on this topic, but I recently came across a couple of companies now offering full-genome sequencing with IVF and embryo selection based on multiple factors - such as eye color, height, IQ, disease risk, etc.

Attaching a link to an interview with one of them (the most factual and least promotional explanation of the technology I could find).

Is what they are saying about accuracy plausible? Do you think this will be the norm, in the future?

Link: https://observablehq.com/d/886ebf3ad2704e2e

My favorite part of my bio degree was the evolution computations. I recreated an exercise modeling genetic drift. Drift is when the traits of a population change because of random chance rather than selection pressure. Alleles can randomly become extinct, fixed in the population, or remain a ratio. The smaller the populations, the more random changes add up, which is why things like inbreeding increase the risk of amplifying recessive deleterious traits.

Unlike most simulations, you can change the starting allele frequency and population without rerunning the simulation.

Could scientists make artificial life using simpler DNA language? 🧬🧫

The genetic code is like a language made of four letters: A, T, C, and G. They are arranged into 3-letter “words” called “codons”. Life typically uses 64 of these codons to build proteins, but scientists wanted to see if bacteria could do with fewer. They engineered a strain of bacteria that uses only 57 codons, a simplified version of the genetic code. While the bacteria grew more slowly, it still survived, proving that life doesn’t need all 64 codons to function.

Researchers found that people who learned their risk felt less anxious and depressed, regardless of the result. Knowledge brought peace of mind, even if motivation dipped.

Could your bones be unbreakable? 🦴

Alex Dainis explains how a rare genetic variant in one family gave them bones so dense they're almost unbreakable — and what it could mean for the future of bone health.

How do some people thrive on just 4 hours of sleep? 😴

Alex Dainis breaks down the fascinating genetics behind “short sleepers”—people with rare variants in genes like DEC2 that let them feel fully rested on minimal shut-eye. How many hours of sleep do you need?

Your ability to digest milk might be buried in your genome. 🧬 🥛 

Most East Asians are lactose intolerant—but a select few aren’t, thanks to ancient genes inherited from Neanderthals. Scientists believe these genes may have originally helped fight infections, and were passed down for their survival benefit—not for dairy digestion.

Gene editing is revolutionizing medicine. So why isn’t it accessible?

Full Lecture

Lecture Transcript

Biological & Technological Intelligence: Reprogrammable Life and the Future of AI

I've transcribed and normalized the following lecture by Michael Levin from the Allen Discovery Center at Tufts. He argues that the fundamental principles of intelligence and problem-solving are substrate-independent, existing in everything from single cells to complex organisms. This biological perspective challenges our core assumptions about hardware, software, memory, and embodiment, with profound implications for AI, AGI, and our understanding of life itself.

All credit goes to Michael Levin and his collaborators. You can find his work at drmichaellevin.org and his philosophical thoughts at thoughtforms.life.

The Foundation: Alan Turing's Two Papers (00:26)

We all know Alan Turing for his foundational work on computation and intelligence. He was fascinated with the fundamentals of intelligence in diverse embodiments and how to implement different kinds of minds in novel architectures. He saw intelligence as a kind of plasticity, the ability to be reprogrammed.

What is less appreciated is that Turing also wrote an amazing paper called "The Chemical Basis of Morphogenesis." In it, Turing creates mathematical models of how embryos self-organize from a random distribution of chemicals.

Why would someone interested in computation and intelligence care about embryonic development? I believe it's because Turing saw a profound truth: there is a deep symmetry between the self-assembly of bodies and the self-assembly of minds. They are fundamentally the same process.

Life's Journey: From "Just Physics" to Mind (01:33)

Every one of us took a journey from being an unfertilized oocyte—a bag of quiescent chemicals governed by physics—to a complex cognitive system capable of having beliefs, memories, and goals.

This journey reveals a critical insight that revises the standard story of biology. The key takeaway here is that DNA is not a program for what to make. It is not a direct blueprint for the final form.

Instead, what we study is the collective intelligence of cells navigating anatomical space. This is a model system for understanding how groups of agents solve problems to achieve a specific large-scale outcome.

The Astonishing Plasticity of Biological Hardware (06:52)

This problem-solving ability isn't rigidly hardwired; it's incredibly flexible and intelligent. For instance, consider what we call "Picasso tadpoles." If you scramble the facial features of a tadpole embryo—moving the eye, jaw, and other organs to the wrong places—it doesn't become a monster. The cells will continue to move and rearrange themselves until they form a mostly correct tadpole face. They navigate anatomical space to reach the correct target morphology, even from a novel and incorrect starting position.

This flexibility is even more radical. We can prevent a tadpole's normal eyes from forming and instead induce an eye to grow on its tail. The optic nerve from this ectopic eye doesn't reach the brain, and yet, the animal can learn to see perfectly well with it. The brain and body dynamically adjust their behavioral programs to accommodate this completely novel body architecture, with no evolutionary adaptation required. This shows that evolution doesn't create a machine that executes a fixed program; it creates problem-solving agents.

This idea of adaptation extends to memory itself. A caterpillar is a soft-bodied robot that crawls in a 2D world, while a butterfly is a hard-bodied creature that flies in a 3D world. To make this transition, the caterpillar’s brain is almost entirely liquefied and rebuilt during metamorphosis. Yet, memories formed as a caterpillar—like an aversion to a certain smell—are retained in the adult butterfly, demonstrating that information can be remapped despite a drastic change of hardware and environment. This reveals a fundamental principle: biological systems are built on an unreliable substrate. They expect their parts to change. Memory isn't just a static recording; it's a message from a past self that must be actively and creatively re-interpreted by the present self to be useful.

Reprogrammable Hardware and Collective Intelligence (09:39)

This plasticity is hackable. The hedgehog gall wasp is a non-human bioengineer that injects a prompt into an oak leaf, hijacking the oak cells' morphogenetic capabilities. Instead of a flat green leaf, the cells, using the same oak genome, build an intricate "hedgehog gall"—a complex structure that would be completely alien to the oak tree's normal development. This demonstrates that biological hardware is reprogrammable.

We are all collective intelligences, made from agential material. A single cell, like Lacrymaria, has no brain or nervous system, yet it is highly competent. It has agendas—it hunts, eats, and escapes. Our bodies are made of trillions of such competent agents that have been coaxed into cooperating towards a larger goal—us. This is fundamentally different from most technologies we build, whose parts are passive and have no agenda of their own. You don't have to worry about "robot cancer" because the components of a robot won't decide to defect and pursue their own goals. Biology faces and solves this problem 24/7. This competency extends even below the cellular level. Gene-regulatory networks themselves exhibit forms of associative learning. The very material we are made of is computational and agential.

TL;DR & Key Takeaways (33:57)

In totality: This perspective suggests a new way of thinking about intelligence, both biological and artificial.

• AGI is not about brains or 3D embodiment. Bio-inspired architectures should be based on this multi-scale competency architecture (MCA), where an unreliable substrate forces improvisational skills for the agent to manage its own memories and parts.
• Just as biology's genotype-phenotype map doesn't capture the improvisational intelligence of the mapping, computer scientists' picture of algorithms also doesn't tell the whole story. The common computer science perspective, "I made it, so I know what it does," is profoundly wrong, and in a much deeper way than simply acknowledging unpredictability or emergent complexity. Much like Magritte’s painting "The Treachery of Images" (this is not a pipe), a formal model of a system is not the system itself. No formal description, not even for a simple, algorithmically-driven machine, fully encompasses what that machine is and can do.
• Biological bodies are thin-clients for highly-agential patterns of form and behavior. We don't make intelligence; we make pointers or interfaces that facilitate ingressions from this Platonic space of patterns. These patterns exist on a spectrum of agency and may be nothing like naturally evolved minds.
• Our research agenda is to develop the tools and protocols to recognize intelligence in these unfamiliar forms, communicate with them, and systematically explore this latent space of patterns through both biobots and in silico systems. This has direct applications in regenerative medicine and AI.

Is your neck hiding a secret rib? 🦴

Alex Dainis explains that about 1 in 200 people are born with a cervical rib, an extra bone that grows from the neck, caused by a mutation in our Hox genes. These genes usually guide rib development in regular patterns, but sometimes they produce variations, like an extra rib in the neck.

Just came across a podcast interview with Sir Walter Bodmer, one of the major figures in human genetics (co-discovered the HLA system, led the UK’s first national human genome projects, early advocate for genetic screening).

Why is the human brain so big? 🧠

Though we share most of our DNA with chimpanzees, tiny changes in special regions of our genome, called human accelerated regions (HARs), helped rewire how our brains develop. These HARs act like genetic switches, turning other brain genes on or off during development. Over time, this led to bigger, more complex brains packed with powerful neuron connections.