Biology

cross-posted from: https://lemmy.sdf.org/post/3152363

Figs and fig wasps have a tightly coordinated reproductive cycle, and have been cospeciating for 70 to 90 million years. The pollination of figs is accomplished in an internal cavity only accessible to a specific species of wasp. The wasp enters through an opening that is only just large enough for it to get through, loosing it's wings and antenna in the process. Pollen on the wasp pollinate the fig's internal flowers, and the wasp lays it's eggs in some of the flowers before dying there. When the male wasps hatch, they fertilize the unhatched females, and burrow tunnels out of the fig before also dying inside it. When the females hatch, they exit the fig through the tunnels, taking pollen with them to search for a fig within which to lay their eggs.

https://en.wikipedia.org/wiki/Syconium https://en.wikipedia.org/wiki/Fig_wasp

Another video by Journey to the Microcosmos, in which they take a look at something else than ciliates, diatoms etc.

The strange science experiment that blew a worm’s head off… and blew our minds.

This interview is an episode from /channel/UCz7Gx6wLCiPw3F-AmXUvH8w, our publication about ideas that inspire a life well-lived, created with the /channel/UCMJ6QeJUbCUuhOSYZadF7sA.

Michael Levin, a developmental biologist at Tufts University, challenges conventional notions of intelligence, arguing that it is inherently collective rather than individual.

Levin explains that we are collections of cells, with each cell possessing competencies developed from their evolution from unicellular organisms. This forms a multi-scale competency architecture, where each level, from cells to tissues to organs, is solving problems within their unique spaces.

Levin emphasizes that properly recognizing intelligence, which spans different scales of existence, is vital for understanding life's complexities. And this perspective suggests a radical shift in understanding ourselves and the world around us, acknowledging the cognitive abilities present at every level of our existence.

Read the video transcript ► https://bigthink.com/the-well/intelligence-can-cells-think/?utm_source=youtube&utm_medium=video&utm_campaign=youtube_description

• https://piped.video/watch?v=U93x9AWeuOA
• https://www.youtube.com/watch?v=U93x9AWeuOA

Now a set of useful mutations are implemented, and balanced so that the number of nodes or edges doesn't explode.

The mutations I've implemented (node are genes are nodes):

add random gene
delete node
delete group of nodes (range of indexes)
split edge    create new node in place of an edge (insertNode)
flip edge
duplicate node
duplicated group of nodes (range of indexes)
change node index (regrouping/separating functional groups)
change group of nodes index (transposable elements)
create random edge
delete random existing edge
scale existing edge weight
negate weight
redirect existing edge to random node
scale parameter (k1, b, k2)
negate bias

This is the next installment from the Gene Regulatory Network saga.

previously: https://lemmy.sdf.org/post/1967056######

cross-posted from: https://lemm.ee/post/4915484

In this video, I talk briefly about a few interesting discoveries and experiments made over the years concerning evolution and natural selection in modern animals with the hope of convincing some people that evolution is indeed real and visible in the real world and that animals can change and evolve over time and in response to environmental conditions entirely naturally. Hope you enjoy!

Chapters:

1. Intro
2. Big Bird: https://en.wikipedia.org/wiki/Big_Bird_(bird)
3. Italian Wall Lizards: https://en.wikipedia.org/wiki/Italian_wall_lizard
4. Stickleback: https://en.wikipedia.org/wiki/Stickleback

• https://piped.video/watch?v=NArlXzSFt2Y
• https://www.youtube.com/watch?v=NArlXzSFt2Y

I'm working on a program to edit and simulate gene regulatory networks using recurrent neural networks as a model. Here's a demo.

cross-posted from: https://lemmy.sdf.org/post/1775532

A model of gene regulatory networks using the mathematical model for recurrent neural nets from computer science. It's such a great way to describe how a cell 'knows' things. every single celled organism or cell in a body contains within a complex information processing chemical network of gene-regulating proteins. One way to think of it is that every individual cell integrates information like a neural network. Good read, there are newer papers on this subject, but I'm not sure if there are better ones.

Based on Neural Model of the Genetic Network Vohradsky 2001 I'm working on a project to make reaction diffusion and evolutionary algorithms more interesting. I want to simulate development of artificial multicellular organisms.