A New Interactive Series for Systems Biology
Announcing a new series of interactive articles explaining introductory concepts in systems biology, starting with transcription networks
I'm excited to introduce a new series on my website, Newt Interactive, focusing on the fascinating world of systems biology, specifically transcription networks. My aim with this series is to break down complex biological concepts into digestible, interactive lessons that will engage both newcomers and those already familiar with the field.
Over the last few months I've been trying to find my own creative way of sharing what I've been learning in biology, and this feels like the right combination of my early passion — building interactive learning content — and my most recent obsession — biology.
I’m beginning with systems biology because it’s an ideal subject for interactive learning. It deals with intricate networks of genes, proteins, and cellular processes that can be challenging to visualize and understand through text alone. I want to bring systems biology concepts to life by incorporating interactive elements, allowing you to manipulate variables and see the results in real-time. Here’s a simple example exploring the Hill function for an activator:
So far, I’ve written three articles as part of an Introduction to Transcription Networks:
Transcription Network Basics: the fundamental concepts of transcription factors and gene expression
Activators and Repressors: the two types of transcription factors and their mathematical models (Hill function)
Dynamics and Response Time: how cells respond to changes in signals and modelling how long that takes
The articles and the series follows along Uri Alon’s textbook, An Introduction to Systems Biology. I’ve been mesmerized by the book and wanted to play around with some of the concepts introduced and also deepen my understanding (especially some of the math), which inspired building this series.
Apart from the interactive chart shown above and the main text of the articles, here are a few features you’ll find in my series:
fun diagrams:
detailed math derivations and explanations:
and yes, more kinds of interactive charts and diagrams:
What’s Coming Up
Several months ago, I learned about FoldIt, a game developed by David Baker’s team at the University of Washington that lets players fold a string of amino acids into protein structures, and get in-game feedback as to whether the folding was correct or not. I downloaded the game and gave it a shot — it was originally released in 2008 and, even with the newer versions, feels a little old now, but it still does a fantastic job of allowing you to “feel” protein folding.
I also learned that Demis Hassabis, the co-founder of DeepMind, played FoldIt in his undergraduate days. In fact, FoldIt was one of the inspirations to decide to use the same technology that was beating Lee Sedol at Go — AlphaGo — to take a crack at protein folding — now known as AlphaFold. (Baker and Hassabis, as you might have heard, were recently awarded the 2024 Nobel Prize for Chemistry for computational protein design, along with John Jumper).
Learning about FoldIt and Hassabis’s role in it was another reminder for me about the importance of games, and how, when done correctly, can have huge long-term impacts. They can be great introductions to complex topics, where players and learners can develop intuition about a topic or problem before having to dive into the, usually, intricate technical details.
These introductory articles are a stepping stone towards creating those complex interactives and educational games in the future. As we go deeper in the series, I want to make more elaborate interactives that visually explain more complicated topics like coherent and incoherent feedforward loops, single input modules (SIMs), and how specific genetic circuitry can enable stability, memory, and oscillation — topics that are the building blocks to understanding relatable experiences like pain, heart beats, and circadian rhythms. I want to work my way up to more sophisticated simulations and tools that will help illustrate more advanced concepts in systems biology and beyond. I want, essentially, to build my own FoldIt.
I believe that this approach – combining clear explanations with hands-on, interactive elements – will make learning about systems biology both more accessible and more fun. Whether you're a student, a professional in a related field, or simply curious about how cells work, I hope you'll find this series informative and enjoyable.
Please subscribe on Newt Interactive if you’re interested in following along (there’s a box at the bottom of the page). I will post regular updates about it here, as well as continue to use this space to write and share pieces that are not interactive-based. If you check it out or find this topic or format interesting, I would love your feedback. I’m also happy to answer any questions or generally just chat!
Additional Links
FoldIt: you can find the game here
How AI Revolutionized Protein Science, but Didn’t End It: A brilliant article by Yasemin Saplakoglu explaining the history of discovering the shape of proteins and how they fold, how that led to advanced computational tools like Rosetta and AlphaFold, and a breakdown of what AIs “solving” protein folding really means. This was where I learned about FoldIt, among many other things. I wrote about it in July but sadly it never left my drafts.