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artificial life

Science Corner: Better with Friends?

How do you think the lower limit on gene number impacts the equilibrium of the 1e-2 result? (Image by Andy Walsh; click to enlarge)

Last week, we talked about gene duplication and looked at some simulation results. For starters, I was just simulating a random walk in the number of genes. The probability of adding a gene (taking a step ‘up’) remained the same, but I varied the probability of losing a gene (taking a step ‘down’). And I prevented the number from ever getting to zero or lower. You can see the results to the right (click for a bigger version). When the probability of losing a gene is 10x higher than gaining (purple/darkest line), the number of genes (averaged over 128 trials) basically stays at 1. No big surprise there; any time a gene is gained, we’d expect to lose it again very quickly before another one is added. Conversely, when the probability of losing a gene is 10x lower than gaining (yellow/lightest line), the average number of genes just keeps on growing; again, not a big surprise. But when the probability of gaining and losing a gene is the same (green/intermediate line), the average number of genes creeps up, possibly leveling off somewhere just above 10. You’d probably expect some kind of equilibrium, but would you have predicted that’s where it would be?
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Science Corner: Better with Friends

A simulation of gene duplication and loss when the genes have no fitness effect. (Image by Andy Walsh; click to enlarge)

Over the weekend, our household reached the point where all of us are fully vaccinated for COVID-19. We celebrated this milestone with an escape room outing. That got me thinking about my little escape room model, the Quandary Den. You can read more details here`, but the short version is that the Quandary Den simulates a game where a player has to “solve” the challenge of the room. My family’s in-person escape room involved lots of combination locks, and here on the blog we simulated some password challenges of a similar sort. In our initial visits to the Quandary Den, we also simulated a challenge where a player had to “solve” the room by tagging the opposing players without getting tagged. That might not seem like much of a puzzle for a real escape room, but when the information about where the opposing players are has to be learned through exploration with feedback, the difficulty goes up a bit. In a real escape room, we can reduce the difficulty (and increase the fun) by adding friends. Does that work in the Quandary Den?
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Science Corner: Unstuck in Neutral

gear shift neutral photo
Couldn’t find one actually in the neutral position. (Photo by brownpau )

Previously in the Quandary Den, I gave you a chance to do some evolutionary artificial life experiments for yourself. I hope you got an opportunity to at least run a couple of different rounds with the simulation. As I mentioned last week, I think simulations like this are a good way to gain experience and build intuition for phenomena we can’t otherwise engage with in daily life. Few of us get to do evolutionary biology in the lab or the field, and some experiments are not possible for anyone due to pragmatic or ethical limitations. But many of us with access to computer resources can play and experiment with simulations like the Quandary Den. In doing so, perhaps you might discover that while evolution is an approach for solving problems, it does not solve all problems equally well.
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Science Corner: Learning by Simulating

simulation photo
Another plus of simulations: you can try new things with little risk. (Photo by OregonDOT )

Last week I introduced you to my escape room/dungeon crawling/superhero training simulation and a few basic results. I don’t want to keep all the fun for myself, so now it’s your turn. I like being able to program so I can make little models and simulations and get “hands-on” with equations and abstract concepts. Some people can look at an equation and understand how changing different parameters will change the results. If there are just two variables, a graph might work. But if there are additional variables or parameters, I find it helpful to make an interactive graph with sliders for the different parameters. Nowadays you can just go to Desmos and get that kind of interactivity, but when I was a student I had to write the programs myself.
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Science Corner: Life Finds a Way Out

A player in our simulated escape room with random instructions. (Click for a bigger version)

What do you with a biologist who isn’t great with living things? In the lab, I tended to kill what needed to stay alive and cultivate contaminating microbes in places that needed to be sterile. Fortunately, I have a knack for getting computers to do what I want. And since evolution has an exploration-with-feedback problem-solving method at its core, it adapts well to computers. Computer scientists, engineers, designers and even artists and musicians have employed problem-solving techniques inspired by biological evolution to answer a variety of questions. But as a biologist, I’m more interested in studying evolution itself rather than using it as a tool to solve some other problem. So I find myself drawn more to artificial life simulations. But what to simulate?
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